Alternatives to Profluent

Evo Designer is a cutting-edge tool created by the Arc Institute, harnessing the power of the Evo 2 genomic foundation model to aid in the generation and analysis of DNA sequences. Users can enter nucleotide sequences or select specific organisms, prompting the model to produce relevant DNA sequences tailored to their needs. This platform also offers detailed annotations of coding regions and provides 3D protein visualizations for prokaryotic sequences through ESMFold, enhancing the understanding of protein structures. In addition to these features, Evo Designer evaluates sequences by calculating their perplexity and per-nucleotide entropy, which helps researchers gauge the complexity and variability of the sequences they are working with. The Evo 2 model at the core of this tool has been trained on an impressive dataset of over 9 trillion nucleotides sourced from a wide variety of prokaryotic and eukaryotic genomes. Utilizing a sophisticated deep learning architecture, it models biological sequences with single-nucleotide precision and boasts a context window that can extend up to 1 million tokens, thereby ensuring high accuracy in sequence representation and analysis. This combination of features makes Evo Designer an invaluable resource for genetic research and exploration.

Evo 2 represents a cutting-edge genomic foundation model that excels in making predictions and designing tasks related to DNA, RNA, and proteins. It employs an advanced deep learning architecture that allows for the modeling of biological sequences with single-nucleotide accuracy, achieving impressive scaling of both compute and memory resources as the context length increases. With a robust training of 40 billion parameters and a context length of 1 megabase, Evo 2 has analyzed over 9 trillion nucleotides sourced from a variety of eukaryotic and prokaryotic genomes. This extensive dataset facilitates Evo 2's ability to conduct zero-shot function predictions across various biological types, including DNA, RNA, and proteins, while also being capable of generating innovative sequences that maintain a plausible genomic structure. The model's versatility has been showcased through its effectiveness in designing operational CRISPR systems and in the identification of mutations that could lead to diseases in human genes. Furthermore, Evo 2 is available to the public on Arc's GitHub repository, and it is also incorporated into the NVIDIA BioNeMo framework, enhancing its accessibility for researchers and developers alike. Its integration into existing platforms signifies a major step forward for genomic modeling and analysis.

Swiss-PdbViewer, also known as DeepView, is a software tool that offers an intuitive interface for the simultaneous analysis of multiple proteins. Users can superimpose these proteins to determine structural alignments and evaluate various critical components, such as active sites. The application simplifies the process of obtaining information on amino acid mutations, hydrogen bonds, angles, and atomic distances through its easy-to-navigate graphical and menu-driven interface. Developed by Nicolas Guex since 1994, Swiss-PdbViewer was originally closely integrated with SWISS-MODEL, an automated homology modeling server created by the Swiss Institute of Bioinformatics (SIB) within the Structural Bioinformatics Group at the Biozentrum in Basel. Over time, the SWISS-MODEL web interface has progressed significantly, allowing for direct use in advanced modeling tasks. As a result, the complexity of maintaining a direct connection with Swiss-PdbViewer has led to the discontinuation of support for that integration. This evolution reflects broader changes in bioinformatics tools and their capabilities.

HyperProtein is the latest offering from Hypercube, Inc., concentrating on the computational analysis of protein sequences. This innovative product not only examines one-dimensional sequences but also delves into the resulting three-dimensional structures of proteins. A key aspect of HyperProtein is its exploration of the intricate relationship between a protein's sequence and its structural form. In contrast to standalone software that targets specific functions like sequence alignment, HyperProtein combines a wide array of Bioinformatics and Molecular Modeling tools, providing a comprehensive approach to the science that begins with a protein sequence. By integrating these diverse tools, HyperProtein aims to enhance the understanding of protein functions and interactions at a molecular level, making it a valuable resource for researchers in the field.

MEGA, which stands for Molecular Evolutionary Genetics Analysis, is an intuitive and highly capable software suite tailored for examining DNA and protein sequence information from various species and populations. It allows for both automated and manual alignment of sequences, the construction of phylogenetic trees, and the testing of evolutionary theories. The software employs an array of statistical approaches such as maximum likelihood, Bayesian inference, and ordinary least squares, making it indispensable for comparative sequence analysis and insights into molecular evolution. Additionally, MEGA includes sophisticated functionalities like real-time caption generation to clarify the findings and methodologies applied during analysis, alongside the maximum composite likelihood method for calculating evolutionary distances. The program is enhanced with powerful visual aids, including an alignment/trace editor and a tree explorer, while also supporting multi-threading to optimize processing efficiency. Furthermore, MEGA is compatible with several operating systems, such as Windows, Linux, and macOS, ensuring accessibility for a diverse user base. In summary, MEGA stands out as a comprehensive tool for researchers delving into the intricacies of molecular genetics.

Correlation Engine serves as an engaging omics knowledgebase designed to situate private omics data within a rich biological framework alongside meticulously curated public datasets. Recognized as one of the most extensive biological databases globally, it offers life science researchers unparalleled access to an immense collection of high-quality whole-genome analyses, complemented by powerful scientific tools. This knowledgebase fosters groundbreaking discoveries by enabling the exploration of billions of data points sourced from standardized whole genome study analyses. It features an array of applications tailored for discerning biological context, a continuously expanding library of curated datasets, and versatility across various species and multi-omic datasets. Users can navigate through an intuitive graphical user interface that facilitates guided workflows, one-click applications, and application programming interfaces (APIs). By streamlining the transition from omic data to actionable insights, researchers can tap into over 25,000 multi-omics studies derived from more than 250,000 unique signatures that have undergone reanalysis, thereby enhancing their research capabilities even further.

Delve into a vast collection of meticulously curated single-cell transcriptome datasets, as well as your own, using dynamic visualizations and analytical tools. This software is versatile, accommodating multimodal omics, CITE-seq, TCR-seq, and spatial transcriptomics. Engage with the most extensive single-cell expression database globally, where you can access and extract insights from a repository featuring millions of fully annotated cells complete with cell type labels and experimental metadata. Beyond merely serving as a conduit to published research, BioTuring Browser functions as a comprehensive end-to-end solution tailored for your specific single-cell data needs. Easily import your fastq files, count matrices, or Seurat and Scanpy objects to uncover the biological narratives contained within. With an intuitive interface, you can access an extensive array of visualizations and analyses, transforming the process of extracting insights from any curated or personal single-cell dataset into a seamless experience. Additionally, the platform allows for the importation of single-cell CRISPR screening or Perturb-seq data, enabling users to query guide RNA sequences with ease. This functionality not only enhances research capabilities but also facilitates the discovery of novel biological insights.

Manage, store, and collaborate on multi-omic datasets effectively. The Illumina Connected Analytics platform serves as a secure environment for genomic data, facilitating the operationalization of informatics and the extraction of scientific insights. Users can effortlessly import, construct, and modify workflows utilizing tools such as CWL and Nextflow. The platform also incorporates DRAGEN bioinformatics pipelines for enhanced data processing. Securely organize your data within a protected workspace, enabling global sharing that adheres to compliance standards. Retain your data within your own cloud infrastructure while leveraging our robust platform. Utilize a versatile analysis environment, featuring JupyterLab Notebooks, to visualize and interpret your data. Aggregate, query, and analyze both sample and population data through a scalable data warehouse, which can adapt to your growing needs. Enhance your analysis operations by constructing, validating, automating, and deploying informatics pipelines with ease. This efficiency can significantly decrease the time needed for genomic data analysis, which is vital when rapid results are essential. Furthermore, the platform supports comprehensive profiling to uncover novel drug targets and identify biomarkers for drug response. Lastly, seamlessly integrate data from Illumina sequencing systems for a streamlined workflow experience.

Geneyx Analysis offers an all-encompassing solution for managing next-generation sequencing (NGS) data, efficiently transforming FASTQ files into clinical reports tailored for both hospital and commercial laboratories. This cutting-edge platform incorporates machine learning and artificial intelligence capabilities to uncover new biomedical insights, enhancing diagnostic efficiency and reducing turnaround times. By delivering a fully transparent and user-friendly interface, Geneyx Analysis empowers clinicians and researchers with complete control over data interpretation and simplifies the challenges associated with managing in-house bioinformatics workflows. Users can customize protocols to suit various gene panels, exomes, and genomes, while our extensive annotation engine facilitates the analysis of all genetic variants, including structural and copy number variations, as well as regulatory elements. In combination, Geneyx Analysis streamlines the diagnostic journey from sequencer output to finalized report, while also serving as a valuable resource for the discovery of novel variants. This platform not only enhances clinical capabilities but also paves the way for groundbreaking research in genomics.

The Bioconductor initiative is dedicated to creating and distributing open-source software for the accurate and reproducible analysis of biological data. We promote a welcoming and cooperative environment for developers and data scientists alike. Our resources are designed to unlock the full potential of Bioconductor. From foundational tools to sophisticated functionalities, our extensive tutorials, guides, and documentation cater to all user needs. Utilizing the R programming language, Bioconductor embraces both open-source principles and collaborative development. It features biannual releases and boasts a vibrant user community. Additionally, Bioconductor offers Docker images for each release and facilitates its integration within AnVIL. Established in 2001, Bioconductor has become a prominent open-source project within the realms of bioinformatics and biomedical research. It encompasses over 2,000 R packages contributed by upwards of 1,000 developers and experiences more than 40 million annual downloads. Furthermore, Bioconductor has been referenced in over 60,000 scientific publications, underscoring its significant impact on the research community. The ongoing growth and evolution of Bioconductor continue to support advancements in biological data analysis.

Created within the Data Sciences Platform at the Broad Institute, this comprehensive toolkit provides an extensive array of features primarily aimed at variant discovery and genotyping. With its robust processing engine and high-performance computing capabilities, it is equipped to manage projects of any magnitude. The GATK has established itself as the industry benchmark for detecting SNPs and indels in both germline DNA and RNA sequencing data. Its functionalities are now broadening to encompass somatic short variant detection as well as addressing copy number variations (CNV) and structural variations (SV). Besides the core variant callers, the GATK incorporates numerous utilities for executing associated tasks, including the processing and quality assurance of high-throughput sequencing data, and it comes bundled with the well-known Picard toolkit. Originally designed for exome and whole genome data generated via Illumina sequencing technology, these tools are versatile enough to be modified for use with various other technologies and study designs. As research evolves, the adaptability of the GATK ensures it remains relevant in diverse genomic investigations.

The innovative XetaBase platform streamlines tertiary analysis by aggregating, indexing, and enriching secondary genomic data, which facilitates ongoing re-evaluation to reveal valuable insights for research and clinical applications. By enhancing data management practices, XetaBase allows for the economical utilization of genomic information both in laboratories and clinical settings. The platform is designed to handle expansive genomic datasets, where increased volume and complexity lead to improved insights and outcomes. Built on the open-source OpenCB software framework, XetaBase is a genomic-native technology that addresses the demands for scalability, speed, and innovative re-interpretation in genomic medicine. Zetta Genomics provides an advanced genomic data management solution tailored for the era of precision medicine. This transformative platform eliminates outdated flat file methods, introducing actionable and relevant genomic data into both laboratory and clinical environments. Furthermore, XetaBase not only supports ongoing re-interpretation but also adapts effortlessly as databases expand to include more comprehensive genome sequences, ensuring that users stay at the forefront of genomic advancements.

The QIAGEN CLC Geneomics Workbench is a powerful tool that works for all workflows. It is easy to overcome data analysis challenges with cutting-edge technology, unique features and algorithms that are widely used by scientists in industry and academia. Bioinformatics software solutions that are user-friendly allow for comprehensive analysis and interpretation of your NGS data. This includes de novo assembly and transcriptome assembly, resequencing analysis, WES and targeted panel support, variant calling, variant calling, RNA–seq, ChIP–seq and DNA methylation analysis (bisulfite sequence analysis). You can analyze your RNA-seq (miRNA, smallRNA) and smallRNA (lncRNA), data using easy-to-use transcriptomics workflows that allow for differential expression analysis at both gene and transcript levels. QIAGEN CLC Genomics Workbench was designed to support a wide variety of NGS bioinformatics programs.

The L7 Enterprise Science Platform (L7|ESP®) is a comprehensive platform designed to contextualize data and remove business silos through process orchestration. This all-in-one solution supports the digitalization of data and scientific processes within life sciences organizations. It includes native applications like L7 LIMS, L7 Notebooks, L7 MES, and L7 Scheduling. L7|ESP seamlessly integrates with third-party applications, lab instruments, and devices to consolidate all data into a unified model. Featuring a low-code/no-code workflow designer and numerous pre-built connectors, it ensures rapid implementation and full automation. Utilizing a single data model, L7|ESP enhances advanced bioinformatics, AI, and ML to provide new scientific and operational insights. L7|ESP addresses the data and lab management needs and challenges within the life sciences sector, specifically targeting: ● Research and Diagnostics ● Pharma and CDMO ● Clinical Sample Management Explore the L7 Resource Center for on-demand recordings, case studies, datasheets, and more: l7informatics dot com/resource-center

Eidogen-Sertanty's Target Informatics Platform (TIP) stands out as the pioneering structural informatics system and knowledgebase that empowers researchers to explore the druggable genome through a structural lens. By harnessing the burgeoning wealth of experimental protein structure data, TIP revolutionizes structure-based drug discovery, shifting it from a limited, low-throughput field to a dynamic and data-rich scientific discipline. It is specifically designed to connect the realms of bioinformatics and cheminformatics, providing drug discovery scientists with a repository of insights that are not only unique but also highly synergistic with the information available from traditional bio- and cheminformatics tools. The platform's innovative combination of structural data management with advanced target-to-lead calculation and analytical capabilities significantly enhances every phase of the drug discovery process. With TIP, researchers are better equipped to navigate the complexities of drug development and make informed decisions.

Designing and simulating cloning procedures with precision is essential for successful outcomes; testing complex projects can help identify potential errors in advance, ensuring that the correct constructs are generated on the first attempt. The process of cloning becomes significantly more manageable when users have clear visibility into their work, thanks to an intuitive interface that streamlines intricate processes. With SnapGene, documentation is automated, relieving users of the burden of manual record-keeping while allowing them to view and share every alteration made during sequence edits and cloning procedures that ultimately resulted in the final plasmid. Enhancing your core molecular biology techniques can lead to better experimental results, and by mastering SnapGene along with essential cloning concepts through the SnapGene Academy, you can elevate your expertise. This online learning platform features over 50 video tutorials conducted by experienced scientific professionals, enabling you to broaden your knowledge across a range of molecular biology subjects. Additionally, the recent SnapGene 7.2 update introduces improved visualization of primer homodimer structures and enhances file management, allowing for better organization of tabs across multiple windows through a user-friendly drag-and-drop feature. This makes it easier than ever to manage your cloning projects efficiently and effectively.

Partek bioinformatics software offers robust statistical and visualization capabilities through a user-friendly interface that caters to researchers of varying expertise. This innovation allows users to navigate genomic data with unprecedented speed and ease, truly embodying our motto, "We turn data into discovery®." With pre-installed workflows and pipelines in a simple point-and-click format, even complex NGS and array analyses become accessible to all scientists. Our combination of custom and public statistical algorithms works seamlessly to transform NGS data into valuable biological insights. Engaging visual tools like genome browsers, Venn diagrams, and heat maps illuminate the intricacies of next-generation sequencing and array data with vibrant clarity. Additionally, our team of Ph.D. scientists is always available to provide support for NGS analyses whenever queries arise. Tailored to meet the demanding computational requirements of next-generation sequencing, the software also offers flexible options for installation and user management, ensuring a comprehensive solution for research needs. As a result, users can focus more on their research and less on technical challenges.

Geneious Prime enhances access to bioinformatics by converting raw datasets into intuitive visual representations that facilitate sequence analysis in a user-friendly manner. It offers straightforward sequence assembly along with the convenient editing of contigs. Users benefit from automatic gene prediction, motif identification, translation, and variant calling through its annotation features. It also allows for the genotyping of microsatellite traces using automated ladder fitting and peak calling, producing comprehensive tables of alleles. The platform showcases beautifully designed visualizations of annotated genomes and assemblies, presented in a customizable sequence view that enhances user experience. Furthermore, it supports powerful analyses of SNP variants, simplifies RNA-Seq expression evaluations, and assists in amplicon metagenomics. Users can also design and test PCR and sequencing primers while developing their own searchable primer database. Additionally, Geneious Biologics provides a versatile, scalable, and secure solution to optimize workflows for antibody analysis, enabling the creation of high-quality libraries and the selection of the most suitable therapeutic candidates. This integration of tools fosters greater efficiency and innovation in biological research.

Transform your single-cell RNA sequencing data into actionable insights using Cellenics software, which is hosted by Biomage as a community instance of this open-source analytics tool developed at Harvard Medical School. This platform empowers biologists to delve into single-cell datasets without the need for coding, while facilitating collaboration between scientists and bioinformaticians. Within just a few hours, it can convert count matrices into publication-ready figures, integrating effortlessly into your existing workflow. Cellenics is designed to be fast, interactive, and user-friendly, as well as being cloud-based, secure, and scalable to meet various research needs. The community instance provided by Biomage is available at no cost for academic researchers working with smaller to medium-sized datasets, accommodating up to 500,000 cells. Currently, over 3000 academic researchers engaged in studies related to cancer, cardiovascular health, and developmental biology are utilizing this powerful tool. This collaborative environment not only enhances research capabilities but also accelerates the discovery process in various scientific fields.

Cease the struggle with cloud infrastructure and unreliable informatics tools; begin uncovering biological insights immediately. The scientific exploration process is hindered by the disjointed nature of tools utilized by biology and bioinformatics teams. To address this issue, we developed a unified bioinformatics platform that bridges the gap between wet lab and dry lab operations in the cloud, enabling teams to expedite their research and development efforts. You can easily import raw data from your cloud, your service provider, or your team's instruments with minimal hassle. Create and implement tailored bioinformatics workflows in various programming languages without the frustration of complex infrastructure management. Effortlessly execute any workflow while maintaining a comprehensive log of every analysis performed. Our platform features ready-to-use interactive visualizations for NGS data that allow you to create point-and-click plots with ease. Additionally, Latch seamlessly integrates with your organization’s AWS S3, granting access to hundreds of terabytes of data within a user-friendly organic filesystem. You can define bioinformatics workflows and dynamically generate no-code interfaces using Python, with adjustable compute and storage options to suit your needs. This innovative approach not only streamlines the research process but also fosters collaboration among teams, ultimately leading to more impactful scientific discoveries.

Sapio Sciences delivers a cutting-edge AI-driven lab informatics platform that integrates Laboratory Information Management Systems (LIMS), Electronic Lab Notebooks (ELN), and a Scientific Data Cloud into one seamless ecosystem. It is tailored to advance scientific research, clinical diagnostics, drug discovery, and manufacturing through configurable, no-code solutions. The Sapio LIMS® automates complex workflows with full configurability, removing the need for programming. Sapio ELN® offers a flexible, adaptable electronic lab notebook that supports diverse experimental needs. The platform’s Scientific Data Cloud consolidates instrument and research data enterprise-wide, paving the way for AI-driven insights. By unifying these components, Sapio simplifies data management and boosts productivity across the lab lifecycle. The platform is accessible for a wide range of industries and research applications. It aims to reduce administrative burden and enhance collaboration within scientific teams.

Combinatorial barcoding technology revolutionizes the outdated limitations of traditional single-cell methodologies. By eliminating the need for specialized instruments, it empowers researchers to make groundbreaking discoveries with ease. This innovation allows for the profiling of anywhere from 1,000 to 1 million cells or nuclei in a single experiment, driving forward unparalleled advancements in science. Evercode combinatorial barcoding technology significantly outperforms droplet-based methods, enabling researchers to increase the scale of their experiments without the constraints of previous technologies. Enjoy enhanced data quality while avoiding the complexities and requirements of outdated hardware. Conduct single-cell experiments using only a pipette and standard laboratory tools, simplifying the process and making it more accessible. The split-pool combinatorial barcoding technique facilitates scalable single-cell analysis without relying on any specialized instruments, making it easier than ever to achieve scalable sequencing. Each kit includes a comprehensive set of reagents and user-friendly analysis software, streamlining the entire workflow from start to finish for optimal efficiency. This technology not only enhances research capabilities but also fosters a new era of accessibility in scientific exploration.

The Illumina DRAGEN Secondary Analysis system offers precise, thorough, and highly efficient processing of next-generation sequencing data. Utilizing a graph reference genome alongside machine learning techniques, it achieves remarkable accuracy. The workflow is exceptionally streamlined, capable of completely analyzing a 34x whole human genome in approximately 30 minutes when using the DRAGEN server v4. Additionally, it enhances this workflow by compressing FASTQ file sizes by up to five times. This system is adept at analyzing a variety of NGS data types, including whole genomes, exomes, methylomes, and transcriptomes. It is designed to be compatible with the user's preferred platform and is scalable to meet varying requirements. DRAGEN analysis consistently ranks as a leader in accuracy for both germline and somatic variant detection, as evidenced by its performance in industry competitions conducted by precisionFDA. This advanced analysis solution empowers laboratories of all sizes and specialties to maximize the potential of their genomic datasets. Moreover, the implementation of highly adaptable field-programmable gate array (FPGA) technology allows DRAGEN to deliver hardware-accelerated genomic analysis algorithms, further enhancing its performance. Such advancements position DRAGEN as a vital tool in the ever-evolving field of genomics.

g.nome is a cloud-native platform designed to offer efficient, scalable, and interoperable workflows tailored for next-generation sequencing analysis. It features a low-code/no-code approach to building pipelines, allowing users to access a curated library of pre-built workflows and toolkits. This empowers researchers to easily import their custom code, manage large datasets with confidence, and enhance collaboration among team members, regardless of their location. By utilizing g.nome, researchers can eliminate longstanding obstacles related to workflow languages, visibility of process flows, and quality assurance. Consequently, they can concentrate entirely on their scientific endeavors, as g.nome transforms the complexities of genomic workflows into streamlined, efficient processes. This innovative platform not only simplifies research but also fosters an environment where scientific inquiry can thrive unhindered.

Introducing IDBS Polar, the pioneering BioPharma Lifecycle Management (BPLM) platform that streamlines tedious manual operations, empowering you to carry out processes more effectively while gathering the essential data needed to speed up market entry by addressing significant hurdles in process design, optimization, scale-up, and technology transfer. This innovative platform features interactive data analytics tools, including a bioreactor comparison tool tailored for biopharma development scientists. IDBS Polar excels at securely overseeing drug progression through comprehensive workflows, seamless integration, and insightful data analysis. Its structured workflows are crafted to ease the complexities of the BioPharma Lifecycle, ensuring process-aware planning, design, and execution of complete bioprocess and analytical unit operations. Meaningful integrations enhance the relevance of your data, while rapid incorporation into your development ecosystem fosters automation and establishes a robust, process-centric data framework. In an industry where precision and efficiency are paramount, IDBS Polar stands out as a vital solution for modern biopharmaceutical development.

Galaxy serves as an open-source, web-based platform specifically designed for handling data-intensive research in the biomedical field. For newcomers to Galaxy, it is advisable to begin with the introductory materials or explore the available help resources. You can also opt to set up your own instance of Galaxy by following the detailed tutorial and selecting from a vast array of tools available in the tool shed. The current Galaxy instance operates on infrastructure generously supplied by the Texas Advanced Computing Center. Furthermore, additional resources are mainly accessible through the Jetstream2 cloud, facilitated by ACCESS and supported by the National Science Foundation. Users can quantify, visualize, and summarize mismatches present in deep sequencing datasets, as well as construct maximum-likelihood phylogenetic trees. This platform also supports phylogenomic and evolutionary tree construction using multiple sequences, the merging of matching reads into clusters with the TN-93 method, and the removal of sequences from a reference that are within a specified distance of a cluster. Lastly, researchers can perform maximum-likelihood estimations to ascertain gene essentiality scores, making Galaxy a powerful tool for various applications in genomic research.

Efficiently address tissue heterogeneity and the intricacies of microenvironments using the GeoMx Digital Spatial Profiler (DSP), which stands out as the most versatile and powerful spatial multi-omic platform for examining both FFPE and fresh frozen tissue sections. Unique among spatial biology platforms, GeoMx allows for non-destructive profiling of RNA and protein expression across various tissue compartments and cell populations, supported by an automated and scalable workflow that seamlessly integrates with conventional histology staining. You can spatially profile the entire transcriptome along with over 570 protein targets, either separately or concurrently, utilizing sample inputs such as whole tissue sections, tissue microarrays (TMAs), or organoids. By choosing GeoMx DSP, you position yourself at the forefront of spatial biology for effective biomarker discovery and hypothesis validation. With the ability to determine the relevant boundaries, you can rely on biology-driven profiling that enables you to focus on the tissue microenvironments and cell types that hold the most significance for your research. This innovative approach ensures that your analyses are both comprehensive and tailored to the specific biological contexts of interest.

Universal Analysis Software (UAS) is a comprehensive platform that facilitates the analysis and management of forensic genomic data, making intricate bioinformatics tasks easier to navigate. This robust solution encompasses a variety of analysis modules that are compatible with all existing ForenSeq workflows, such as ForenSeq MainstAY, ForenSeq Kintelligence, ForenSeq DNA Signature Prep, ForenSeq mtDNA Whole Genome, and ForenSeq mtDNA Control Region. With UAS, users can swiftly generate FASTQ files, execute alignment processes, and identify forensically significant variants from next-generation sequencing (NGS) data. The software's extensive validation ensures highly dependable variant calls, providing precise outcomes in an accessible format without the burden of per-seat licensing fees. Tailored specifically for forensic analysts, UAS optimizes the management of base-by-base sequence data, offering a wide array of features that support everything from the efficient review of standard STR profiles to in-depth analysis of the most complex samples, thus enhancing the overall efficiency of forensic investigations.

Proteins, which are remarkably complex machines, play a crucial role not only in the biological functions of your body but also in every living organism's processes. They serve as the fundamental units of life. As of now, there are approximately 100 million identified proteins, with discoveries being made regularly. Each protein possesses a distinctive three-dimensional shape that is essential to its functionality and purpose. However, determining a protein's precise structure is often a costly and lengthy endeavor, resulting in an understanding of only a small percentage of the proteins recognized by science. Addressing this growing disparity and developing methods to predict the structures of millions of yet-to-be-discovered proteins could significantly advance our ability to combat diseases, expedite the discovery of new treatments, and potentially unveil the secrets of life's mechanisms. The implications of such advancements could transform both medicine and our understanding of biology.

3decision® serves as a cloud-based repository for protein structures, focusing on efficient management of structural data and offering sophisticated analytics to support teams involved in the discovery of small molecules and biologics, thereby expediting the process of structure-based drug design. The platform consolidates and standardizes both experimental and computational protein structures sourced from publicly available databases such as RCSB PDB and AlphaFoldDB, in addition to proprietary datasets, and accommodates formats like PDBx/mmCIF and ModelCIF. This comprehensive approach guarantees seamless access to a variety of structural formats including X-Ray, NMR, cryo-EM, and modeled structures, thereby promoting collaboration and bolstering research initiatives. In addition to its storage capabilities, 3decision® enhances each entry with valuable metadata and sequence information, which encompasses details on protein-ligand interactions, antibody annotations, and specifics about binding sites. Equipped with advanced analytical instruments, the platform is capable of pinpointing druggable sites, evaluating off-target risks, and facilitating comparisons of binding sites, which collectively transform extensive structural datasets into practical insights that can drive research forward. Furthermore, its cloud-based architecture fosters enhanced collaboration among research teams, making it easier for scientists to share findings and insights, ultimately leading to more innovative approaches in drug discovery and development.

BioNeMo is a cloud service and framework for drug discovery that leverages AI, built on NVIDIA NeMo Megatron, which enables the training and deployment of large-scale biomolecular transformer models. This service features pre-trained large language models (LLMs) and offers comprehensive support for standard file formats related to proteins, DNA, RNA, and chemistry, including data loaders for SMILES molecular structures and FASTA sequences for amino acids and nucleotides. Additionally, users can download the BioNeMo framework for use on their own systems. Among the tools provided are ESM-1 and ProtT5, both transformer-based protein language models that facilitate the generation of learned embeddings for predicting protein structures and properties. Furthermore, the BioNeMo service will include OpenFold, an advanced deep learning model designed for predicting the 3D structures of novel protein sequences, enhancing its utility for researchers in the field. This comprehensive offering positions BioNeMo as a pivotal resource in modern drug discovery efforts.

Orbit BioSequence from Questel is an advanced tool for intellectual property (IP) intelligence, tailored to assist researchers, patent experts, and biotech firms in the thorough analysis and management of biological sequence data within the IP realm. This software presents a sophisticated framework for scrutinizing, analyzing, and keeping track of nucleotide and protein sequences identified in patent documents, thereby providing users with unprecedented access to vital sequence information that is essential for fostering innovation and conducting competitive assessments. With Orbit BioSequence, users can execute highly precise similarity and identity searches throughout international patent databases, empowering organizations to pinpoint existing patents, mitigate infringement risks, and discover potential licensing or collaboration opportunities. Furthermore, the software employs state-of-the-art search algorithms alongside meticulously curated datasets, guaranteeing both accuracy and relevance in the results. The comprehensive nature of this tool positions it as an invaluable resource in the evolving landscape of biotechnology and intellectual property management.

OmicsBox, a leading bioinformatics tool, offers end-toend data analysis for genomes, transcriptomes and metagenomes. It also provides genetic variation studies. The application, which is used by leading private and public research institutes worldwide, allows researchers to process large and complicated data sets and streamline their analytical process. It is designed to be efficient, user-friendly and equipped with powerful tools to extract biological insight from omics data. The software is divided into modules, each of which has a set of tools and features designed to perform specific types of analyses, such as de novo genome assemblies, genetic variations analysis, differential expression analyses, taxonomic classifications, and taxonomic classes of microbiome, including the interpretation of results and rich visualizations. The functional analysis module uses the popular Blast2GO annotating methodology, making OmicsBox a great tool for non-model organisms research.

Pluto was founded in 2021 by the Wyss Institute of Harvard University. It has been a trusted partner for many life sciences organizations across the country, from biotech start-ups and public biopharma companies. Our cloud-based platform allows scientists to manage all their data, run bioinformatics analysis, and create interactive visualizations that are published-quality. The platform is being used for a variety of biological applications. These include preclinical and translational science research, cell and gene therapies and drug discovery and development.

Seqera is an innovative bioinformatics platform crafted by the team behind Nextflow, aimed at optimizing and improving the oversight of scientific data analysis workflows. It provides a robust array of tools, such as the Seqera Platform for managing scalable data pipelines, Seqera Pipelines that grant access to a handpicked selection of open-source workflows, Seqera Containers to facilitate container management, and Seqera Studios that create interactive environments for data analysis. The platform is designed to integrate smoothly with a variety of cloud and on-premises systems, promoting reproducibility and compliance within scientific research. Users can incorporate Seqera into their existing infrastructures, including major cloud services like AWS, GCP, and Azure, all without the need for mandatory migrations. This flexibility allows for total control over data residency while enabling global scalability, ensuring that security and performance are never compromised. Furthermore, Seqera empowers researchers to enhance their analytical capabilities while maintaining a seamless operational flow within their established systems.

Efficient data management and streamlined bioinformatics solutions are essential for laboratories that are either just beginning or rapidly expanding their next-generation sequencing (NGS) capabilities. As an integral part of the BaseSpace Suite, BaseSpace Sequence Hub serves as a seamless extension to your Illumina instruments. The encrypted data transmission from these instruments into BaseSpace Sequence Hub simplifies the management and analysis of your data through a selection of specialized analysis applications. Built on the robust Amazon Web Services (AWS), BaseSpace Sequence Hub prioritizes security, ensuring a safe environment for your data. It allows users to initiate sequencing runs and monitor the quality of instrument operations effectively. This system enhances productivity by converting sequencing data into a standardized format and facilitating direct cloud streaming. Additionally, it grants access to necessary computational resources without the need for significant investments in on-premises infrastructure. Ultimately, it boosts organizational efficiency by providing easy access to a wide array of genomic analysis applications, whether developed by you, Illumina, or third-party providers, thus fostering innovation and progress in genomic research.

Collaborating closely with our in-house teams of chemists and biologists, as well as our clients, we create products that excel in both performance and scientific insight. Chemaxon's diverse product lineup includes ready-to-use solutions for researchers, backend resources for IT professionals, additional components for enhanced functionality, and seamless integrations that allow our technology to be accessed through third-party applications such as Microsoft Excel and KNIME. With a user base exceeding one million, Chemaxon has established itself as a leader in developing software that facilitates scientific innovation through advanced calculation, searching, and drawing capabilities. Our tools are extensively utilized in life sciences research and educational settings, serving a broad spectrum of industries, including numerous major pharmaceutical companies. We maintain a global presence with offices in Budapest, Basel, Boston, and San Diego, supported by a network of distributors worldwide. Our commitment to scientific excellence ensures that we remain at the forefront of technological advancements in the life sciences sector.

Choose two tailored cell groups by utilizing metadata to uncover their most significantly differentially expressed genes. Utilize the extensive collection of millions of cells from the integrated CZ CELLxGENE corpus for in-depth analysis. Conduct interactive examinations of datasets to investigate how gene expression patterns are influenced by spatial, environmental, and genetic variables through an intuitive no-code user interface. Gain insights into existing datasets or leverage them as a foundation to discover new cell subtypes and states. Census offers the capability to access any customized segment of standardized cell data available within CZ CELLxGENE, with opportunities for exploration in both R and Python. Delve into an interactive encyclopedia containing over 700 cell types that includes comprehensive definitions, marker genes, lineage information, and associated datasets all in one location. Additionally, you can browse and obtain hundreds of standardized data collections along with more than 1,000 datasets that detail the functionality of both healthy mouse and human tissues, enriching your research and understanding of cellular biology. This resource provides a valuable tool for researchers aiming to enhance their exploration of cellular dynamics and gene expression.

Ruffus is a Python library designed for creating computation pipelines, known for being open-source, robust, and user-friendly, making it particularly popular in scientific and bioinformatics fields. This tool streamlines the automation of scientific and analytical tasks with minimal hassle and effort, accommodating both simple and extremely complex pipelines that might confuse traditional tools like make or scons. It embraces a straightforward approach without relying on "clever magic" or pre-processing, focusing instead on a lightweight syntax that aims to excel in its specific function. Under the permissive MIT free software license, Ruffus can be freely utilized and incorporated, even in proprietary applications. For optimal performance, it is advisable to execute your pipeline in a separate “working” directory, distinct from your original data. Ruffus serves as a versatile Python module for constructing computational workflows and requires a Python version of 2.6 or newer, or 3.0 and above, ensuring compatibility across various environments. Moreover, its simplicity and effectiveness make it a valuable tool for researchers looking to enhance their data processing capabilities.

At Metabolon, we proudly provide the most extensive Level 1 library in the metabolomics field. Our unique library has been meticulously developed and refined over two decades, boasting more than 5,400 entries. The majority of these entries are classified as Level 1, comprising roughly 85% (around 4,600 entries); however, about 15% of the library consists of Level 2 entries (approximately 800 entries), which are categorized as such due to the unavailability of commercial standards necessary for Level 1 classification. Thanks to our unparalleled library size and exceptional annotation confidence, Metabolon offers precise and highly actionable insights tailored to our clients’ scientific or clinical needs. The applications of metabolomics span a broad spectrum of research areas, including soil health, nutritional studies, preclinical investigations, and clinical trials. Whether you're identifying trends within a population or fine-tuning an individual's treatment plan, metabolomics serves as a powerful tool to uncover crucial answers to pressing questions in various fields. With such extensive resources at your disposal, the potential for discovery is truly limitless.

Rather than overseeing your own data centers, leverage Microsoft's extensive experience and scale in managing exabyte-level workloads. With Microsoft Genomics hosted on Azure, you gain access to the performance and scalability of a top-tier supercomputing facility, available on-demand in the cloud environment. Benefit from a backend network that boasts MPI latency of less than three microseconds and a non-blocking throughput of 32 gigabits per second (Gbps). This advanced network features remote direct memory access technology, allowing parallel applications to effectively scale to thousands of cores. Azure equips you with high memory and HPC-class CPUs designed to accelerate your results significantly. You can easily adjust your resources up or down according to your needs and only pay for what you consume, helping to manage costs efficiently. Address data sovereignty concerns with Azure's global network of data centers while ensuring compliance with regulatory requirements. Integration into your current pipeline is seamless, thanks to a REST-based API along with a straightforward Python client, making it easy to enhance your workflows. Additionally, this flexibility allows you to respond swiftly to changing demands in your projects.

Outdated research and development software significantly hinders scientific innovation, causing delays in progress, fragmenting data into isolated systems, and erasing valuable institutional knowledge. In contrast, Benchling stands out as the premier cloud solution for life sciences R&D, facilitating the acceleration, measurement, and forecasting of research activities from the initial discovery phase through bioprocessing, all within a single platform. This comprehensive suite comprises seven seamlessly integrated applications designed to enhance R&D efficiency across various levels. With a focus on codeless configuration, open integration, and customizable dashboards, Benchling meets the unique needs of its users. Furthermore, its profound expertise in life sciences R&D and consulting guarantees long-term success for teams. As a cohesive R&D platform, Benchling allows researchers to minimize time spent on data entry and retrieval, enabling them to collaborate more effectively and advance their studies. Scientists, project managers, and executives alike can improve R&D productivity through enhanced visibility into experimental contexts, overall program performance, and resource allocation. Ultimately, embracing a modern R&D platform like Benchling can transform the way teams approach scientific discovery and innovation.

Loupe Browser stands out as a robust visualization tool, offering the user-friendly capabilities essential for delving into and interpreting 10x Genomics Chromium and Visium datasets. Additionally, the LoupeR package facilitates the transformation of Seurat objects into files compatible with Loupe Browser. The interactive features of the Loupe Browser interface are exemplified through its use of a lung squamous cell carcinoma dataset. Central to the user experience is the view panel, where individual points, each representing cell barcodes, are displayed across multiple projections. Each point typically corresponds to a single cell’s barcode, enabling focused analysis. The t-SNE plot generated by the cell ranger pipeline serves as the default projection, while alternative visualization options are also accessible. Users can effortlessly reposition the plot by dragging the mouse over the cells and can zoom in or out using the mouse wheel or trackpad. Moreover, as the mouse hovers over the plot, cluster labels become visible, which proves particularly beneficial when working with datasets that contain numerous precomputed clusters. This capability enhances the analytical experience, making it easier to identify and interpret complex data patterns.

Precision, efficiency, and assurance. The integration of generative AI into the biopharmaceutical industry is here. This technology streamlines the arduous task of gathering, organizing, and analyzing extensive data sets. Achieve essential insights with complete assurance every single time. With our AI-driven platform for data handling and validation, you will keep your workflows organized effortlessly. Collect, process, and verify your data all from a single interface. Easily search through both public and private databases using key characteristics of drugs. Categorize drugs and clinical trials based on comprehensive patient demographics. Retrieve necessary data in straightforward language. Strengthen your conclusions by linking your findings to their original sources. Direct your focus towards creating valuable outputs from your data, bypassing the tedious manual sorting process. Our advanced language models empower researchers to conduct asset evaluations 4.8 times quicker than traditional methods. We provide access to an extensive index of over 38 million scientific articles, conference papers, and clinical trial data. With this system, you’ll have all the information you require at your fingertips, ensuring timely and informed decision-making. Additionally, our platform adapts to your unique needs, enhancing the research experience even further.

StarDrop™, a comprehensive suite of integrated software, delivers the best in silico technology within a highly visual interface. StarDrop™, which allows seamless flow between the latest data, predictive modeling, and decision-making regarding the next round or synthesis, improves the speed, efficiency and productivity of the discovery process. A balance of different properties is essential for successful compounds. StarDrop™, which guides you through the multi-parameter optimization challenge, helps you target compounds with the highest chance of success. It also saves you time and resources by allowing you to synthesize fewer compounds and test them less often.