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https://bioconductor.org/packages/release/bioc/html/ComplexHeatmap.html

Software package to arrange multiple heatmaps and support various annotation graphics. Used to visualize associations between different sources of data sets and to reveal potential patterns.

Proper citation: ComplexHeatmap (RRID:SCR_017270) Copy   

•   Source: SciCrunch Registry

https://swissmodel.expasy.org/

Software tool as fully automated protein structure homology modeling server, accessible via ExPASy web server, or from program DeepView Swiss Pdb-Viewer. Structural bioinformatics web-server dedicated to homology modeling of 3D protein structures. Used to make protein modelling accessible to all biochemists and molecular biologists.

Proper citation: SWISS-MODEL (RRID:SCR_018123) Copy   

•   Source: SciCrunch Registry

https://signor.uniroma2.it/

Software application to organize and store in structured format signaling information published in scientific literature. Information is stored as binary causative relationships between biological entities and can be represented graphically as activity flow. Each relationship is linked to literature reporting experimental evidence. Each node is annotated with chemical inhibitors that modulate its activity. Signaling information is mapped to human proteome. SIGNOR 2.0 stores manually annotated causal relationships between proteins and other biologically relevant entities including chemicals, phenotypes, complexes, etc with compliance to FAIR data principles.

Proper citation: SIGNOR (RRID:SCR_018485) Copy   

•   Source: SciCrunch Registry

https://github.com/FRED-2/OptiType

Software tool for precision HLA typing from next generation sequencing data.

Proper citation: OptiType (RRID:SCR_022279) Copy   

•   Source: SciCrunch Registry

https://github.com/lkmklsmn/DrivAER

Software tool as method for identification of driving transcriptional programs based on AutoEncoder derived Relevance scores. Infers relevance scores for transcriptional programs with respect to specified outcomes of interest in single-cell RNA sequencing data, such as psuedotemporal ordering or disease status.Used for manifold interpretation in scRNA-seq data.

Proper citation: DrivAER (RRID:SCR_019076) Copy   

•   Source: SciCrunch Registry

https://pm4ngs.readthedocs.io/

Software tool to generate standard organizational structure for Next Generation Sequencing data analysis. Includes directory structure for project, several Jupyter notebooks for data management and CWL workflows for pipeline execution.

Proper citation: PM4NGS (RRID:SCR_019164) Copy   

•   Source: SciCrunch Registry

http://omicslab.genetics.ac.cn/GOEAST/

Gene Ontology Enrichment Analysis Software Toolkit (GOEAST) is a web based software toolkit providing easy to use, visualizable, comprehensive and unbiased Gene Ontology (GO) analysis for high-throughput experimental results, especially for results from microarray hybridization experiments. The main function of GOEAST is to identify significantly enriched GO terms among give lists of genes using accurate statistical methods. Compared with available GO analysis tools, GOEAST has the following unique features: * GOEAST supports analysis for data from various resources, such as expression data obtained using Affymetrix, illumina, Agilent or customized microarray platforms. GOEAST also supports non-microarray based experimental data. The web-based feature makes GOEAST very user friendly; users only have to provide a list of genes in correct formats. * GOEAST provides visualizable analysis results, by generating graphs exhibiting enriched GO terms as well as their relationships in the whole GO hierarchy. * Note that GOEAST generates separate graph for each of the three GO categories, namely biological process, molecular function and cellular component. * GOEAST allows comparison of results from multiple experiments (see Multi-GOEAST tool). The displayed color of each GO term node in graphs generated by Multi-GOEAST is the combination of different colors used in individual GOEAST analysis. Platform: Online tool

Proper citation: GOEAST - Gene Ontology Enrichment Analysis Software Toolkit (RRID:SCR_006580) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.biol.uoa.gr/PRED-TMBB/

A web tool, based on a Hidden Markov Model, capable of predicting the transmembrane beta-strands of the gram-negative bacteria outer membrane proteins, and of discriminating such proteins from water-soluble ones when screening large datasets. The model is trained in a discriminative manner, aiming at maximizing the probability of the correct prediction rather than the likelihood of the sequences. The training is performed on a non-redundant database consisting of 16 outer membrane proteins (OMP''s) with their structures known at atomic resolution. We show that we can achieve predictions at least as good comparing with other existing methods, using as input only the amino-acid sequence, without the need of evolutionary information included in multiple alignments. The method is also powerful when used for discrimination purposes, as it can discriminate with a high accuracy the outer membrane proteins from water soluble in large datasets, making it a quite reliable solution for screening entire genomes. This web-server can help you run a discriminating process on any amino-acid sequence and thereafter localize the transmembrane strands and find the topology of the loops.

Proper citation: PRED-TMBB (RRID:SCR_006190) Copy   

•   Source: SciCrunch Registry

http://genetrail.bioinf.uni-sb.de/

A web-based application that analyzes gene sets for statistically significant accumulations of genes that belong to some functional category. Considered category types are: KEGG Pathways, TRANSPATH Pathways, TRANSFAC Transcription Factor, GeneOntology Categories, Genomic Localization, Protein-Protein Interactions, Coiled-coil domains, Granzyme-B clevage sites, and ELR/RGD motifs. The web server provides two statistical approaches, "Over-Representation Analysis" (ORA) comparing a reference set of genes to a test set, and "Gene Set Enrichment Analysis" (GSEA) scoring sorted lists of genes., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GeneTrail (RRID:SCR_006250) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.intec.ugent.be/magic/

Web based interface for exploring and analyzing a comprehensive maize-specific cross-platform expression compendium. This compendium was constructed by collecting, homogenizing and formally annotating publicly available microarrays from Gene Expression Omnibus (GEO), and ArrayExpress.

Proper citation: Magic (RRID:SCR_006406) Copy   

•   Source: SciCrunch Registry

http://www.bioinsilico.org/cgi-bin/CAPSDB/staticHTML/home

It is a structural classification of helix-cappings or caps compiled from protein structures. Caps extracted from protein structures have been structurally classified based on geometry and conformation and organized in a tree-like hierarchical classification where the different levels correspond to different properties of the caps. CASP-DB is fully browsable and searchable and is regularly updated. The regions of the polypeptide chain immediately preceding or following a helix are known as Nt- and Ct cappings, respectively. Cappings play a central role stabilizing helices due to lack of intrahelical hydrogen bonds in the first and last turn. Sequence patterns of amino acid type preferences have been derived for cappings but the structural motifs associated to them are still unclassified. CAPS-DB is a database of clusters of structural patterns of different capping types. The clustering algorithm is based in the geometry and the space conformation of these regions. CAPS-DB is a relational database that allows the user to search, browse, inspect and retrieve structural data associated to cappings. The contents of CAPS-DB might be of interest to a wide range of scientist covering different areas such as protein design and engineering, structural biology and bioinformatics. CapsDB v4.0 * PDB structures: 4591 * Number of clusters: 859 * Number of caps: 31452

Proper citation: CAPS Database (RRID:SCR_006862) Copy   

•   Source: SciCrunch Registry

http://scop.mrc-lmb.cam.ac.uk/scop/

The Structural Classification of Proteins (SCOP) database is a comprehensive ordering of all proteins of known structure, according to their evolutionary and structural relationships. Protein domains in SCOP are hierarchically classified into families, superfamilies, folds and classes. The continual accumulation of sequence and structural data allows more rigorous analysis and provides important information for understanding the protein world and its evolutionary repertoire. SCOP participates in a project that aims to rationalize and integrate the data on proteins held in several sequence and structure databases. As part of this project, starting with release 1.63, we have initiated a refinement of the SCOP classification, which introduces a number of changes mostly at the levels below superfamily. The pending SCOP reclassification will be carried out gradually through a number of future releases. In addition to the expanded set of static links to external resources, available at the level of domain entries, we have started modernization of the interface capabilities of SCOP allowing more dynamic links with other databases.

Proper citation: SCOP: Structural Classification of Proteins (RRID:SCR_007039) Copy   

•   Source: SciCrunch Registry

https://myhits.sib.swiss/

Database devoted to protein domains. It is also a collection of tools for the investigation of the relationships between protein sequences and motifs described on them.

Proper citation: MyHits (RRID:SCR_006757) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.biol.uoa.gr/cuticleDB

A relational database containing all structural proteins of Arthropod cuticle identified to date. Many come from direct sequencing of proteins isolated from cuticle and from sequences from cDNAs that share common features with these authentic cuticular proteins. It also includes proteins from the five sequenced genomes where manual annotation has been applied to cuticular proteins: Anopheles gambiae, Apis mellifera, Bombyx mori, Drosophila melanogaster, and Nasonia vitripennis. Some sequences were confirmed as authentic cuticular proteins because protein sequencing revealed that they were present in cuticle; others were identified by sequence homology and other criteria. Entries provides information about whether sequences are putative or authentic cuticular proteins. CuticleDB was primarily designed to contain correct and full annotation of cuticular protein data. The database will be of help to future genome annotators. Users will be able to test hypotheses for the existence of known and also of yet unknown motifs in cuticular proteins. An analysis of motifs may contribute to understanding how proteins contribute to the physical properties of cuticle as well as to the precise nature of their interaction with chitin.

Proper citation: CuticleDB (RRID:SCR_007045) Copy   

•   Source: SciCrunch Registry

http://atlasgeneticsoncology.org/

Online journal and database devoted to genes, cytogenetics, and clinical entities in cancer, and cancer-prone diseases. Its aim is to cover the entire field under study and it presents concise and updated reviews (cards) or longer texts (deep insights) concerning topics in cancer research and genomics.

Proper citation: Atlas of Genetics and Cytogenetics in Oncology and Haematology (RRID:SCR_007199) Copy   

•   Source: SciCrunch Registry

http://www.disprot.org/

The Database of Protein Disorder (DisProt) is a curated database that provides information about proteins that lack fixed 3D structure in their putatively native states, either in their entirety or in part. Users can BLAST sequences, browse by protein name, or view by protein function and functional subclass.

Proper citation: DisProt - Database of Protein Disorder (RRID:SCR_007097) Copy   

•   Source: SciCrunch Registry

http://gbrowse.org/

A database and interactive web site for manipulating and displaying annotations on genomes. Features include: detailed views of the genome; use of a variety of premade or personally made glyphs ; customizable order and appearance of tracks by administrators and end-users; search by annotation ID, name, or comment; support of third party annotation using GFF formats; DNA and GFF dumps; connectivity to different databases, including BioSQL and Chado; and a customizable plug-in architecture (e.g. run BLAST, find oligonucleotides, design primers, etc.). GBrowse is distributed as source code for Macintosh OS X, UNIX and Linux platforms, and as pre-packaged binaries for Windows machines. It can be installed using the standard Perl module build procedure, or automated using a network-based install script. In order to use the net installer, you will need to have Perl 5.8.6 or higher and the Apache web server installed. The wiki portion accepts data submissions.

Proper citation: GBrowse (RRID:SCR_006829) Copy   

•   Source: SciCrunch Registry

http://www.expasy.org/ch2d/

A database of proteins identified by various 2-D PAGE and SDS-PAGE reference maps. Each SWISS-2DPAGE entry contains textual data on one protein, including mapping procedures, physiological and pathological information, experimental data (isoelectric point, molecular weight, amino acid composition, peptide masses) and bibliographical references. In addition to this textual data, SWISS-2DPAGE provides several 2-D PAGE and SDS-PAGE images showing the experimentally determined location of the protein, as well as a theoretical region computed from the sequence protein, indicating where the protein might be found in the gel. Using the database, users can locate these proteins on the 2-D PAGE maps or display the region of a 2-D PAGE map where one might expect to find a protein from UniProtKB/Swiss-Prot.

Proper citation: SWISS-2DPAGE (RRID:SCR_006946) Copy   

•   Source: SciCrunch Registry

http://www.agbase.msstate.edu/

A curated, open-source, web-accessible resource for functional analysis of agricultural plant and animal gene products. Our long-term goal is to serve the needs of the agricultural research communities by facilitating post-genome biology for agriculture researchers and for those researchers primarily using agricultural species as biomedical models. AgBase provides tools designed to assist with the analysis of proteomics data and tools to evaluate experimental datasets using the GO. Additional tools for sequence analysis are also provided. We use controlled vocabularies developed by the Gene Ontology (GO) Consortium to describe molecular function, biological process, and cellular component for genes and gene products in agricultural species. AgBase will also accept annotations from any interested party in the research communities. AgBase develops freely available tools for functional analysis, including tools for using GO. We appreciate any and all questions, comments, and suggestions. AgBase uses the NCBI Blast program for searches for similar sequences. And the Taxonomy Browser allows users to find the NCBI defined taxon ID for or taxon name for different organisms.

Proper citation: AgBase (RRID:SCR_007547) Copy   

•   Source: SciCrunch Registry

http://www.hubmed.org/

HubMed provides an interface to PubMed. Quick access to searches with a Firefox search plugin or a HubMed bookmarklet (drag to your browser''s bookmarks toolbar). Export citations in RIS, BibTeX, RDF and MODS formats, or directly to RefWorks. Unzip HubMed''s import filter into Endnote''s Filters folder for direct import into Endnote, or install the RIS Export plugin for direct import into ProCite, RefMan and older versions of Endnote. Use the Citation Finder to convert reference lists from PDFs into search results. Create lists of closely related papers using Rank Relations, then visualise and browse clusters of related papers using TouchGraph (requires Java). Graph occurrences of keywords in published papers over time. Tag and store annotated metadata for articles of interest.

Proper citation: HubMed (RRID:SCR_007296) Copy   

•   Source: SciCrunch Registry