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https://docs.igdiscover.se/en/stable/

Software to analyze antibody repertoires and discover new V genes from high-throughput sequencing reads.Heavy chains, kappa and lambda light chains are supported (to discover VH, VK and VL genes)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: IgDiscover (RRID:SCR_024037) Copy   

•   Source: SciCrunch Registry

https://data.broadinstitute.org/alkesgroup/BOLT-LMM/

Software statistical tool for identifying genetic associations. Used for genome wide association studies in large cohorts.

Proper citation: BOLT-LMM (RRID:SCR_023978) Copy   

•   Source: SciCrunch Registry

https://github.com/sanger-pathogens/iva

Software tool as de novo assembler designed to assemble virus genomes that have no repeat sequences,using Illumina read pairs sequenced from mixed populations at extremely high and variable depth.

Proper citation: IVA (RRID:SCR_024044) Copy   

•   Source: SciCrunch Registry

http://contra.stanford.edu/contrafold/

Software novel secondary structure prediction method based on conditional log-linear models, a flexible class of probabilistic models which generalize upon SCFGs by using discriminative training and feature-rich scoring. Used for sequence prediction.

Proper citation: CONTRAfold (RRID:SCR_023994) Copy   

•   Source: SciCrunch Registry

http://codonw.sourceforge.net

Software tool designed to simplify Multivariate analysis (correspondence analysis) of codon and amino acid usage. It also calculates standard indices of codon usage.

Proper citation: CodonW (RRID:SCR_023989) Copy   

•   Source: SciCrunch Registry

https://biocore.github.io/emperor/

Web browser enabled tool with versatile command line interface to perform exploratory investigations of 3D visualizations of microbial community data, such as principal coordinates plots. EMPeror includes set of controllers to modify features as function of metadata. Web interactive next generation tool for analysis, visualization and understanding of high throughput microbial ecology datasets.

Proper citation: EMPeror (RRID:SCR_024013) Copy   

•   Source: SciCrunch Registry

https://embossgui.sourceforge.net/

Web based graphical user interface to the EMBOSS suite of bioinformatics tools.

Proper citation: EMBOSS explorer (RRID:SCR_024014) Copy   

•   Source: SciCrunch Registry

https://github.com/rrwick/Filtlong

Software tool for filtering long reads by quality.Can take set of long reads and produce smaller, better subset. Uses both read length and read identity when choosing which reads pass the filter.

Proper citation: Filtlong (RRID:SCR_024020) Copy   

•   Source: SciCrunch Registry

http://www.ctsim.org

Software tool to simulate process of transmitting X-rays through phantom objects. Reconstructs original phantom image from projections. Has wide array of image analysis and image processing functions.

Proper citation: CTSim (RRID:SCR_024004) 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://gopubmed.org/web/gopubmed/

A web server which allows users to explore PubMed search results with the Gene Ontology, a hierarchically structured vocabulary for molecular biology. GoPubMed submits a user''''s keywords to PubMed, retrieves the abstracts, detects Gene Ontology terms in the abstracts, displays the subset of Gene Ontology relevant to the original query, and allows the user to browse through the ontology displaying associated papers and their GO annotation. Platform: Online tool

Proper citation: GoPubMed (RRID:SCR_005823) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/expressionprofiler/

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 2, 2016. The EP:GO browser is built into EBI's Expression Profiler, a set of tools for clustering, analysis and visualization of gene expression and other genomic data. With it, you can search for GO terms and identify gene associations for a node, with or without associated subnodes, for the organism of your choice.

Proper citation: Expression Profiler (RRID:SCR_005821) 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://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://bioapps.rit.albany.edu/MITOPRED/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. It predicts nuclear-encoded mitochondrial proteins from all eukaryotic species including plants. Prediction is based on the occurrence patterns of Pfam domains (version 16.0) in different cellular locations, amino acid composition and pI value differences between mitochondrial and non-mitochondrial locations. Additionally, you may download MITOPRED predictions for complete proteomes. Re-calculated predictions are instantly accessible for proteomes of Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila, Homo sapiens, Mus musculus and Arabidopsis species as well as all the eukaryotic sequences in the Swiss-Prot and TrEMBL databases. Queries, at different confidence levels, can be made through four distinct options: (i) entering Swiss-Prot/TrEMBL accession numbers; (ii) uploading a local file with such accession numbers; (iii) entering protein sequences; (iv) uploading a local file containing protein sequences in FASTA format. The Mitopred algorithm works based on the differences in the Pfam domain occurrence patters and amino acid composition differences in different cellular compartments. Location specific Pfam domains have been determined from the entire eukaryotic set of Swissprot database. Similarly, differences in the amino acid composition between mitochondrial and non-mitochondrial sequences were pre-calculated. This information is used to calculate location-specific amino acid weights that are used to calculate amino acid score. Similarly, pI average values of the N-terminal 25 residues in different cellular location were also determined. This knowledge-base is accessed by the program during execution.

Proper citation: mitopred (RRID:SCR_006135) 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://bioinformatics.istge.it/cldb/indexes.html

Hypertext on cell culture availability extracted from the Cell Line Data Base of the Interlab Project. HyperCLDB includes links to records of OMIM, the Online Mendelian Inheritance in Man Catalogue, and now also links to the PubMed, database of bibliographic biomedical references, which are drawn primarily from MEDLINE and PREMEDLINE.

Proper citation: Hyper Cell Line Database (RRID:SCR_007730) Copy   

•   Source: SciCrunch Registry

http://iresite.org/

Database of experimentally verified IRES structures. Presents information about experimentally studied Internal Ribosome Entry Site segments.

Proper citation: IRESite (RRID:SCR_007753) Copy   

•   Source: SciCrunch Registry

http://gump.qimr.edu.au/general/daleN/SNPSpD/

SNPSpD is a method of correcting for non-independance of single nucleotide polymorphisms (SNPs) in linkage disequilibrium (LD) with each other, on the basis of the spectral decomposition (SpD) of matrices of LD between SNP''s. Additionally, output from SNPSpD includes eigenvalues, principal-component coefficients, and factor loadings after varimax rotation, enabling the selection of a subset of SNPs that optimize the information in a genomic region.

Proper citation: Single Nucleotide Polymorphism Spectral Decomposition (SNPSpD) (RRID:SCR_008621) Copy   

•   Source: SciCrunch Registry