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http://www.syfpeithi.de/

SYFPEITHI is a database comprising more than 7000 peptide sequences known to bind class I and class II MHC molecules. The entries are compiled from published reports only. It contains a collection of MHC class I and class II ligands and peptide motifs of humans and other species, such as apes, cattle, chicken, and mouse, for example, and is continuously updated. Searches for MHC alleles, MHC motifs, natural ligands, T-cell epitopes, source proteins/organisms and references are possible. Hyperlinks to the EMBL and PubMed databases are included. In addition, ligand predictions are available for a number of MHC allelic products. The database is based on previous publications on T-cell epitopes and MHC ligands. It contains information on: -Peptide sequences -anchor positions -MHC specificity -source proteins, source organisms -publication references Since the number of motifs continuously increases, it was necessary to set up a database which facilitates the search for peptides and allows the prediction of T-cell epitopes. The prediction is based on published motifs (pool sequencing, natural ligands) and takes into consideration the amino acids in the anchor and auxiliary anchor positions, as well as other frequent amino acids. The score is calculated according to the following rules: The amino acids of a certain peptide are given a specific value depending on whether they are anchor, auxiliary anchor or preferred residue. Ideal anchors will be given 10 points, unusual anchors 6-8 points, auxiliary anchors 4-6 and preferred residues 1-4 points. Amino acids that are regarded as having a negative effect on the binding ability are given values between -1 and -3. Sponsors: SYFPEITHI is supported by DFG-Sonderforschungsbereich 685 and theEuropean Union: EU BIOMED CT95-1627, BIOTECH CT95-0263, and EU QLQ-CT-1999-00713.

Proper citation: SYFPEITHI: A Database for MHC Ligands and Peptide Motifs (RRID:SCR_013182) Copy   

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http://epsf.bmad.bii.a-star.edu.sg/cube/db/html/home.html

Cube-DB is a database of pre-evaluated conservation and specialization scores for residues in paralogous proteins belonging to multi-member families of human proteins. Protein family classification follows (largely) the classification suggested by HUGO Gene Nomenclature Committee. Sets of orhtologous protein sequences were generated by mutual-best-hit strategy using full vertebrate genomes available in Ensembl. The scores, described on documentation page, are assigned to each individual residue in a protein, and presented in the form of a table (html or downloadable xls formats) and mapped, when appropriate, onto the related structure (Jmol, Pymol, Chimera).

Proper citation: Cube-DB (RRID:SCR_013233) Copy   

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https://unicarb-db.expasy.org/

International effort which has created a glycomics knowledgebase with access to a database of information on the glycan structures of glycoproteins. It serves as and promotes an online information storage and search platform for glycomics and glycobiology research. Open access knowledgebase offers resource supported by querying interfaces, annotation technologies and the adoption of common standards to integrate structural, experimental and functional data.

Proper citation: UniCarbKB (RRID:SCR_014410) Copy   

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http://cryptodb.org/cryptodb/

An integrated genomic and functional genomic database for the parasite Cryptosporidium. CryptoDB integrates whole genome sequence and annotation along with experimental data and environmental isolate sequences provided by community researchers. The database includes supplemental bioinformatics analyses and a web interface for data-mining. Organisms included in CryptoDB are Cryptosporidium parvum, Cryptosporidium hominis, Cryptosporidium muris and environmental isolate sequences from numerous species. CryptoDB is allied with the databases PlasmoDB and ToxoDB via ApiDB, an NIH/NIAID-funded Bioinformatics Resource Center. Tools include: * BLAST: Identify Sequence Similarities * Sequence Retrieval: Retrieve Specific Sequences using IDs and coordinates * PubMed and Entrez: View the Latest Cryptosporidium Pubmed and Entrez Results * Genome Browser: View Sequences and Features in the genome browser * CryptoCyc: Explore Automatically Defined Metabolic Pathways * Searches via Web Services: Web service access to our data

Proper citation: ApiDB CryptoDB (RRID:SCR_013455) Copy   

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http://snpeff.sourceforge.net/SnpSift.html

Software toolkit for filtering and manipulating annotated files. After annotation, the software's filter function can find relevant genomic variants in large data files.

Proper citation: SnpSift (RRID:SCR_015624) Copy   

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https://opentrials.net/

Database that contains data such as registry entries, portions of regulatory documents describing individual trials, structured data on methods and results, and researchers and papers from and/or related to clinical trials. The initiative aims to locate, match, and share all publicly accessible data and documents, on all trials conducted, on all medicines and other treatments, globally.

Proper citation: Open Trials (RRID:SCR_015570) Copy   

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http://gnomad.broadinstitute.org/

Database that aggregates exome and genome sequencing data from large-scale sequencing projects. The gnomAD data set contains individuals sequenced using multiple exome capture methods and sequencing chemistries. Raw data from the projects have been reprocessed through the same pipeline, and jointly variant-called to increase consistency across projects.

Proper citation: Genome Aggregation Database (RRID:SCR_014964) Copy   

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https://github.com/stamatak/ExaML

Source code for large-scale phylogenetic analyses on whole-transcriptome and whole-genome alignments using supercomputers.

Proper citation: Examl (RRID:SCR_016087) Copy   

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http://www.lncrnadb.org/

Searchable database of comprehensive annotations of eukaryotic long non-coding RNAs. Entries are manually curated from referenced literature.

Proper citation: lncRNAdb (RRID:SCR_015491) Copy   

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https://web.expasy.org/abcd/

Repository of sequenced antibodies, integrating curated information about antibody and its antigen with cross links to standardized databases of chemical and protein entities. Manually curated repository of sequenced antibodies, developed by Geneva Antibody Facility at University of Geneva, in collaboration with CALIPHO and Swiss Prot groups at SIB Swiss Institute of Bioinformatics. Database provides list of sequenced antibodies with their known targets. Each antibody is assigned unique ID number that can be used in academic publications to increase reproducibility of experiments.

Proper citation: ExPASy ABCD database (RRID:SCR_017401) Copy   

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http://smithlabresearch.org/software/methbase/

Central reference methylome database created from public BS-seq datasets. Provides methylation level at individual sites, regions of allele specific methylation, hypo- or hyper-methylated regions, partially methylated regions, and detailed meta data and summary statistics.

Proper citation: MethBase (RRID:SCR_017487) Copy   

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https://signalingpathways.org

Web multi omics knowledgebase based upon public, manually curated transcriptomic and cistromic datasets involving genetic and small molecule manipulations of cellular receptors, enzymes and transcription factors. Integrated omics knowledgebase for mammalian cellular signaling pathways. Web browser interface was designed to accommodate numerous routine data mining strategies. Datasets are biocurated versions of publically archived datasets and are formatted according to recommendations of the FORCE11 Joint Declaration on Data Citation Principles73, and are made available under Creative Commons CC 3.0 BY license. Original datasets are available.

Proper citation: Signaling Pathways Project (RRID:SCR_018412) Copy   

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http://bioen-compbio.bioen.illinois.edu/FusionHunter/

Software for identifying fusion transcripts using paired-end RNA-seq.

Proper citation: FusionHunter (RRID:SCR_011895) Copy   

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https://www.integromics.com/omicsoffice-for-ngs/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 18,2025. Software for secondary and tertiary analysis of Next Generation Sequencing (NGS) data.

Proper citation: OmicsOffice for NGS SeqSolve (RRID:SCR_001222) Copy   

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http://www.bioinfor.com/zoom/general/overview.html

Software to map the Illumina/Solexa reads of 15x coverage of a human genome to the reference human genome in one CPU-day, allowing two mismatches, at full sensitivity.

Proper citation: ZOOM (RRID:SCR_002175) Copy   

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http://segway.hoffmanlab.org/

The free Segway software package contains a novel method for analyzing multiple tracks of functional genomics data. The method uses a dynamic Bayesian network (DBN) model, which enables it to analyze the entire genome at 1-bp resolution even in the face of heterogeneous patterns of missing data. This method is the first application of DBN techniques to genome-scale data and the first genomic segmentation method designed for use with the maximum resolution data available from ChIP-seq experiments without downsampling. Segway uses the Graphical Models Toolkit (GMTK) for efficient DBN inference. The software has extensive documentation and was designed from the outset with external users in mind.

Proper citation: Segway - a way to segment the genome (RRID:SCR_004206) Copy   

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http://www.biopieces.org

A collection of bioinformatics tools that can be pieced together in a very easy and flexible manner to perform both simple and complex tasks. The Biopieces work on a data stream in such a way that the data stream can be passed through several different Biopieces, each performing one specific task: modifying or adding records to the data stream, creating plots, or uploading data to databases and web services. The Biopieces are executed in a command line environment where the data stream is initialized by specific Biopieces which read data from files, databases, or web services, and output records to the data stream that is passed to downstream Biopieces until the data stream is terminated at the end of the analysis. The advantage of the Biopieces is that a user can easily solve simple and complex tasks without having any programming experience. Moreover, since the data format used to pass data between Biopieces is text based, different developers can quickly create new Biopieces in their favorite programming language - and all the Biopieces will maintain compatibility. Finally, templates exist for creating new Biopieces in Perl and Ruby. There are currently ~190 Biopieces (March 2014).

Proper citation: Biopieces (RRID:SCR_005783) Copy   

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http://www.biochem.ucl.ac.uk/bsm/virus_database/VIDA3/VIDA.html

VIDA contains a collection of homologous protein families derived from open reading frames from complete and partial virus genomes. For each family, users can get an alignment of the conserved regions, functional and taxonomy information, and links to DNA sequences and structures. * Search homologous protein families from particular virus families * Links to complete genome sequence: Arteriviridae, Coronaviridae, Herpesviridae, Poxviridae The Virus Database at University College London has been developed as a system to organize animal virus open reading frame sequences. All known and predicted protein sequences from complete and partial genomes of particular virus families are extracted from GenBank and filtered to remove 100% redundancy. On the basis of sequence similarity the sequences are then clustered into homologous protein families (HPFs). The families are enriched with annotations including function and functional classification, related protein structures, taxonomy, length of the proteins, boundaries of the conserved region/s, virus-specific gene name and links to EMBL entries and SWISSPROT., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: VIDA (RRID:SCR_007111) Copy   

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http://cudasw.sourceforge.net/

CUDASW++ is a bioinformatics software for Smith-Waterman protein database searches that takes advantage of the massively parallel CUDA architecture of NVIDIA Tesla GPUs to perform sequence searches 10x-50x faster than NCBI BLAST. In this algorithm, we deeply explore the SIMT (Single Instruction, Multiple Thread) and virtualized SIMD (Single Instruction, Multiple Data) abstractions to achieve fast speed. This algorithm has been fully tested on Tesla C1060, Tesla C2050, GeForce GTX 280 and GTX 295 graphics cards, and has been incorporated to NVIDIA Tesla Bio Workbench. * Operating System: Linux * Programming language: CUDA and C * Other requirements: CUDA SDK and Toolkits 2.0 or higher

Proper citation: CUDASW++ (RRID:SCR_008862) Copy   

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https://gitlab.com/kyrgyzov/lsa_slurm

Software tool to implement pre-assembly binning scheme leveraging sparse dictionary learning and matrix factorization to solve sparse decomposition problems arising in field of metagenomics.

Proper citation: lsa_slurm (RRID:SCR_018134) Copy   

•   Source: SciCrunch Registry