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https://compbio.dfci.harvard.edu/predictivenetworks//

A flexible, open-source, web-based application and data services framework that enables the integration, navigation, visualization and analysis of gene interaction networks. The primary goal of PN is to allow biomedical researchers to evaluate experimentally derived gene lists in the context of large-scale gene interaction networks. The PN analytical pipeline involves two key steps. The first is the collection of a comprehensive set of known gene interactions derived from a variety of publicly available sources. The second is to use these ''known'' interactions together with gene expression data to infer robust gene networks. The regression-based network inference algorithm creates a graph of gene interactions in which cycles may be present (but no self-loops). Based on information-theoretic techniques, a causal gene interaction network is inferred from both prior knowledge (interactions extracted from biomedical literature and structured biological databases) and gene expression data. A prediction model is fitted for each gene, given its parents, enabling assessment of the predictive ability of the network model.

Proper citation: Predictive Networks (RRID:SCR_006110) Copy   

•   Source: SciCrunch Registry

http://ccb.jhu.edu/software/hisat2/index.shtml

Graph-based alignment of next generation sequencing reads to a population of genomes.

Proper citation: HISAT2 (RRID:SCR_015530) Copy   

•   Source: SciCrunch Registry

http://www.iu.edu/~beca/

Visualization and analysis software for interactive visual exploration and mining of fiber-tracts and brain networks with their genetic determinants and functional outcomes. BECA includes an fMRI and Diseases Analysis version as well as a Genome Explorer version.

Proper citation: BECA (RRID:SCR_015846) Copy   

•   Source: SciCrunch Registry

http://www.rostlab.org/cms/

A lab organization which has bases in Munich, Germany and at Columbia University and focuses its research on protein structure and function using sequence and evolutionary information. They utilize machine learning and statistical methods to analyze genetic material and its gene products. Research goals of the lab involve using protein and DNA sequences along with evolutionary information to predict aspects of the proteins relevant to the advance of biomedical research.

Proper citation: ROSTLAB (RRID:SCR_000792) Copy   

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http://ccb.jhu.edu/software/sim4cc/

Software tool as cross species spliced alignment program.Heuristic sequence alignment tool for comparing cDNA sequence with genomic sequence containing homolog of gene in another species.

Proper citation: sim4cc (RRID:SCR_001204) Copy   

•   Source: SciCrunch Registry

http://www.genesigdb.org

Database of traceable, standardized, annotated gene signatures which have been manually curated from publications that are indexed in PubMed. The Advanced Gene Search will perform a One-tailed Fisher Exact Test (which is equivalent to Hypergeometric Distribution) to test if your gene list is over-represented in any gene signature in GeneSigDB. Gene expression studies typically result in a list of genes (gene signature) which reflect the many biological pathways that are concurrently active. We have created a Gene Signature Data Base (GeneSigDB) of published gene expression signatures or gene sets which we have manually extracted from published literature. GeneSigDB was creating following a thorough search of PubMed using defined set of cancer gene signature search terms. We would be delighted to accept or update your gene signature. Please fill out the form as best you can. We will contact you when we get it and will be happy to work with you to ensure we accurately report your signature. GeneSigDB is capable of providing its functionality through a Java RESTful web service.

Proper citation: GeneSigDB (RRID:SCR_013275) Copy   

•   Source: SciCrunch Registry

http://www.i2b2.org

i2b2 (Informatics for Integrating Biology and the Bedside) is an NIH-funded National Center for Biomedical Computing based at Partners HealthCare System. The i2b2 Center is developing a scalable informatics framework that will enable clinical researchers to use existing clinical data for discovery research and, when combined with IRB-approved genomic data, facilitate the design of targeted therapies for individual patients with diseases having genetic origin. For some resources (e.g. software) the use of the resource requires accepting a specific (e.g. OpenSource) license.

Proper citation: Informatics for Integrating Biology and the Bedside (RRID:SCR_013629) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/pmc/about/pubreader/

A web application which serves as an alternate way to read scientific literature in PubMed Central and Bookshelf. PubReader features an easy-to-read multi-column display, a figure strip for access to figures, and a search function. It is designed especially to support reading on tablets and other smaller devices but is available for reading on laptops and desktops.

Proper citation: PubReader (RRID:SCR_013814) Copy   

•   Source: SciCrunch Registry

http://ligand-expo.rutgers.edu/

An integrated data resource for finding chemical and structural information about small molecules bound to proteins and nucleic acids within the structure entries of the Protein Data Bank. Tools are provided to search the PDB dictionary for chemical components, to identify structure entries containing particular small molecules, and to download the 3D structures of the small molecule components in the PDB entry. A sketch tool is also provided for building new chemical definitions from reported PDB chemical components.

Proper citation: Ligand Expo (RRID:SCR_006636) Copy   

•   Source: SciCrunch Registry

https://wiki.nci.nih.gov/display/LexEVS/LexGrid

LexGrid (Lexical Grid) provides support for a distributed network of lexical resources such as terminologies and ontologies via standards-based tools, storage formats, and access/update mechanisms. The Lexical Grid Vision is for a distributed network of terminological resources. It is the foundation of the National Center for Biomedical Ontology BioPortal interface and web-services, and can parse OBO format, as well as other formats such as OWL. Currently, there are many terminologies and ontologies in existence. Just about every terminology has its own format, its own set of tools, and its own update mechanisms. The only thing that most of these pieces have in common with each other is their incompatibility. This makes it very hard to use these resources to their full potential. We have designed the Lexical Grid as a way to bridge terminologies and ontologies with a common set of tools, formats and update mechanisms. The Lexical Grid is: * accessible through a set of common APIs * joined through shared indices * online accessible * downloadable * loosely coupled * locally extendable * globally revised * available in web-space on web-time * cross-linked The realization of this vision requires three interlocking components, which are: * Standards - access methods and formats need to be published and openly available * Tools - standards based tools must be readily available * Content - commonly used terminologies have to be available for access and download Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: LexGrid (RRID:SCR_006627) Copy   

•   Source: SciCrunch Registry

http://www.nlm.nih.gov/research/umls/

Database of key terminology, classification and coding standards, and associated resources to promote creation of more effective and interoperable biomedical information systems and services, including electronic health records. This set of files and software brings together many health and biomedical vocabularies and standards to enable interoperability between computer systems. Users can use the UMLS to enhance or develop applications, such as electronic health records, classification tools, dictionaries and language translators. The UMLS has three tools, which we call the Knowledge Sources: * Metathesaurus: Terms and codes from many vocabularies, including CPT, ICD-10-CM, LOINC, MeSH, RxNorm, and SNOMED CT * Semantic Network: Broad categories (semantic types) and their relationships (semantic relations) * SPECIALIST Lexicon and Lexical Tools: Natural language processing tools We use the Semantic Network and Lexical Tools to produce the Metathesaurus. Metathesaurus production involves: * Processing the terms and codes using the Lexical Tools * Grouping synonymous terms into concepts * Categorizing concepts by semantic types from the Semantic Network * Incorporating relationships and attributes provided by vocabularies * Releasing the data in a common format Although we integrate these tools for Metathesaurus production, you can access them separately or in any combination according to your needs. The UMLS Terminology Services (UTS) provides three ways to access the UMLS: Web Browsers, Local Installation, and Web Services APIs.

Proper citation: Unified Medical Language System (RRID:SCR_006363) Copy   

•   Source: SciCrunch Registry

https://evidencemodeler.github.io/

Software tool for automated eukaryotic gene structure annotation that reports eukaryotic gene structures as weighted consensus of all available evidence. Used to combine ab intio gene predictions and protein and transcript alignments into weighted consensus gene structures. Inputs include genome sequence, gene predictions, and alignment data (in GFF3 format).

Proper citation: EVidenceModeler (RRID:SCR_014659) Copy   

•   Source: SciCrunch Registry

https://www.ccpn.ac.uk/v2-software/software/extras/datamodelfolder

Model to cover data for macromolecular NMR spectroscopy from the initial experimental data to the final validation. Used for the large scale data deposition, data mining and program interoperability. Enables movement from one software package to another without difficulties with data conversion or loss of information. Works with CcpNmr Analysis software for analysis and interactive display, CcpNmr FormatConverter for allowing transfer of data from programs used in NMR to and from the Data Model, and the CLOUDS software for automated structure calculation and assignment. Used within the CCPN software suite for NMR spectroscopy and at the BioMagResBank for converting existing deposited restraint lists to a standard IUPAC nomenclature.

Proper citation: CCPN Data Model (RRID:SCR_016982) Copy   

•   Source: SciCrunch Registry

https://www.robotreviewer.net/about

Open source web based system that uses machine learning and NLP to semi automate biomedical evidence synthesis, to aid practice of Evidence Based Medicine. Processes full text journal articles describing randomized controlled trials. Designed to automatically extract key data items from reports of clinical trials.

Proper citation: RobotReviewer (RRID:SCR_021064) Copy   

•   Source: SciCrunch Registry

https://glimmpse.samplesizeshop.org/#/

Web based software tool that calculates power and sample size for study designs with normally distributed outcomes. Permits power calculations for clinical trials, randomized experiments, and observational studies with clustering, repeated measures, and both, and almost any testable hypothesis. GLIMMPSE Version 3 release back end has been refactored in Python, interface has been simplified, requiring user decisions about only one topic per screen, new menu improves specification of both between-participant and within-participant hypothese, recursive algorithm permits computing covariances for up to ten levels of clustering., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GLIMMPSE (RRID:SCR_016297) Copy   

•   Source: SciCrunch Registry

http://www.wwpdb.org/

Public global Protein Data Bank archive of macromolecular structural data overseen by organizations that act as deposition, data processing and distribution centers for PDB data. Members are: RCSB PDB (USA), PDBe (Europe) and PDBj (Japan), and BMRB (USA). This site provides information about services provided by individual member organizations and about projects undertaken by wwPDB. Data available via websites of its member organizations.

Proper citation: Worldwide Protein Data Bank (wwPDB) (RRID:SCR_006555) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/guide/sitemap/

The National Center for Biotechnology Information''s listing of resources. Sort by alphabetical character, Databases, Downloads, Submissions, Tools and How-To; or by Topic: Chemicals & Bioassays; Data & Software; DNA & RNA; Domains & Structures; Genes & Expression; Genetics & Medicine; Genomes & Maps; Homology; Literature; Proteins; Sequence Analysis; Taxonomy; Training & Tutorials; Variation.

Proper citation: NCBI Resource List (RRID:SCR_005628) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/biosample

Database containing descriptions of biological source materials used in experimental assays. Sources include: GenBank, Sequence Read Archive (SRA), Coriell, ATCC. Submissions are supported by a web-based Submission Portal that guides users through a series of forms for input of rich metadata describing their samples. As the capacity and complexity of biological data sets expands, databases face new challenges in ensuring that the information is adequately organized and described. The NCBI BioSample database is being developed to help address the challenges by providing the means by which data generators can organize and describe a broad range of sample types, and link to corresponding sets of experimental data in archival databases.

Proper citation: NCBI BioSample (RRID:SCR_004854) Copy   

•   Source: SciCrunch Registry

http://nmr.cmbi.ru.nl/NRG-CING/HTML/index.html

NRG-CING presents a complete validation report for all 9,000+ wwPDB NMR entries including remediated experimental data such as chemical shifts from BMRB and restraints from NRG . These CING reports are compiled from internal analyses and those by CCPN, DSSP, PROCHECK-NMR/Aqua, ShiftX, Talos+, Vasco, Wattos, and WHAT_CHECK. The NRG-CING website is a collection of CING reports that has been pre-calculated for all PDB files solved by NMR. (See website for more information on CING.) In case the underlying experimental data is available, these have been cleaned up and made syntactically and semantically correct and homogeneous. For many macromolecular NMR ensembles from the Protein Data Bank (PDB) the experiment-based restraint lists used in the structure calculation are accessible, while other experimental data, mainly chemical shift values, are often available from the BioMagResBank. Assessment of the quality of the structural result is paramount to their usage and a combined, integrated repository of both input data and structural results greatly facilitates such an analysis. In addition, the accuracy and precision of the coordinates in these macromolecular NMR ensembles can be improved by recalculations using the available experimental data and present-day software with improved protocols and force fields. Such efforts, however, generally fail on over half of all deposited structures due to the syntactic and semantic heterogeneity of the data and the wide variety of formats used for their deposition. We have combined the cleaned-up restraints information from the NMR Restraints Grid (NRG) database with available chemical shifts from the BioMagResBank in the weekly updated NRG-CING database. Eleven programs, in addition to CING itself, have been included in the NRG-CING production pipeline to arrive at validation reports that list for each entry the potential inconsistencies between the coordinates and the available restraint and chemical shift data. The longitudinal validation of this data yielded a set of indicators that can be used to judge the quality of every macromolecular structure solved with NMR. The cleaned up NMR experimental datasets and the validation reports are freely available.

Proper citation: NRG-CING (RRID:SCR_006079) Copy   

•   Source: SciCrunch Registry

http://lussierlab.org/GO-Module/GOModule.cgi

GO-Module provides an interface to reduce the dimensionality of GO enrichment results and produce interpretable biomodules of significant GO terms organized by hierarchical knowledge that contain only true positive results. Users can download a text file of GO terms annotated with their significance and identified biomodules, a network visualization of resultant GO IDs or terms in PDF format, and view results in an online table. Platform: Online tool

Proper citation: GO-Module (RRID:SCR_005813) Copy   

•   Source: SciCrunch Registry