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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://wwwmgs.bionet.nsc.ru/mgs/programs/panalyst/

WebProAnalyst provides web-accessible analysis for scanning the quantitative structure-activity relationships in protein families. It searches for a sequence region, whose substitutions are correlated with variations in the activities of a homologous protein set, the so-called activity modulating sites. WebProAnalyst allows users to search for the key physicochemical characteristics of the sites that affect the changes in protein activities. It enables the building of multiple linear regression and neural networks models that relate these characteristics to protein activities. WebProAnalyst implements multiple linear regression analysis, back propagation neural networks and the Structure-Activity Correlation/Determination Coefficient (SACC/SADC). A back propagation neural network is implemented as a two-layered network, one layer as input, the other as output (Rumelhart et al, 1986). WebProAnalyst uses alignment of amino acid sequences and data on protein activity (pK, Km, ED50, among others). The input data are the numerical values for the physicochemical characteristics of a site in the multiple alignment given by a slide window. The output data are the predicted activity values. The current version of WebProAnalyst handles a single activity for a single protein. The SACC/SADC may be defined as an estimate of the strongest multiple correlation between the physicochemical characteristics of a site in a multiple alignment and protein activities. The SACC/SADC coefficient makes possible the calculation of the possible highest correlation achievable for the quantitative relationship between the physicochemical properties of sites and protein activities. The SACC/SADC is a convenient means for an arrangement of positions by their functional significance. WebProAnalyst outputs a list of multiple alignment positions, the respective correlation values, also regression analysis parameters for the relationships between the amino acid physicochemical characteristics at these positions and the protein activity values.

Proper citation: Webproanalyst (RRID:SCR_008348) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/synergyfinder/

Software R package as efficient implementations for all popular synergy scoring models for drug combinations, including HSA, Loewe, Bliss and ZIP and visualization of synergy scores as either two dimensional or three dimensional interaction surface over dose matrix. Used to calculate and visualize synergy scores for drug combinations.

Proper citation: SynergyFinder (RRID:SCR_019318) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/fgsea/

Software R package for fast preranked gene set enrichment analysis. Allows to make more permutations and get more fine grained p-values, which allows to use accurate stantard approaches to multiple hypothesis correction.

Proper citation: fgsea (RRID:SCR_020938) Copy   

•   Source: SciCrunch Registry

https://github.com/pensoft/omicsdatapaper

Software package for streamlined import of omics metadata from European Nucleotide Archive into OMICS Data Paper manuscript. Omics Data Paper R Shiny app demonstrates workflow for automatic import of ENA genomic metadata into omics data paper manuscript. Streamlined conversion of metadata into manuscript facilitates authoring of omics data papers, which allow omics dataset creators to receive credit for their work and to improve description and visibility of their datasets.

Proper citation: Omics Data Paper Generator (RRID:SCR_019809) Copy   

•   Source: SciCrunch Registry

https://github.com/slzarate/parliament2

Software tool to identify structural variants in given sample relative to reference genome. Runs combination of tools to generate structural variant calls on whole genome sequencing data.

Proper citation: Parliament2 (RRID:SCR_019187) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/variancePartition/

Software R package to quantify and interpret divers of variation in multilevel gene expression experiments.Provides statistical and visualization framework for studying drivers of variation in RNA-seq datasets in many types of high throughput genomic assays including RNA-seq gene-, exon- and isoform-level quantification, splicing efficiency, protein quantification, metabolite quantification, metagenomic assays, methylation arrays and epigenomic sequencing assays.

Proper citation: variancePartition (RRID:SCR_019204) Copy   

•   Source: SciCrunch Registry

https://sydneybiox.github.io/CiteFuse/

Software R package consisting of suite of tools for doublet detection, modality integration, clustering, differential RNA and protein expression analysis, antibody-derived tag evaluation, ligand-receptor interaction analysis and interactive web-based visualization of CITE-seq data.

Proper citation: CiteFuse (RRID:SCR_019321) Copy   

•   Source: SciCrunch Registry

https://guoweilong.github.io/BS_Seeker2/index.html

Software tool as versatile aligning pipeline for bisulfite sequencing data. Used for mapping bisulfite sequencing data and generating DNA methylomes. Improves mappability over existing aligners by using local alignment. Maps reads from RRBS library by building special indexes with improved efficiency and accuracy. Provides additional function for filtering out reads with incomplete bisulfite conversion, which is useful in minimizing overestimation of DNA methylation levels.

Proper citation: Bs-Seeker2 (RRID:SCR_020948) Copy   

•   Source: SciCrunch Registry

https://github.com/pavanvidem/chira

Software tool suite to analyze RNA-RNA interactome experimental data such as CLASH, CLEAR-CLIP, PARIS, SPLASH, etc.

Proper citation: ChiRA (RRID:SCR_019219) Copy   

•   Source: SciCrunch Registry

https://edspace.american.edu/openbehavior/project/facesync/, https://bio.tools/FaceSync

Project related to emotions and facial expressions. Includes open source guide to building affordable head mount for camera to maintain high temporal and spatial resolution of face throughout duration of experiment. Device is paired with FaceSync, Python toolbox which automatically synchronizes recorded facial expressions to videos and events such as social interactions.

Proper citation: FaceSync project (RRID:SCR_021393) Copy   

•   Source: SciCrunch Registry

http://gepat.sourceforge.net/

A web-based software tool offering an integrated analysis of transcriptome data under genomic, proteomic and metabolic context.

Proper citation: GEPAT (RRID:SCR_003597) Copy   

•   Source: SciCrunch Registry

http://jexpress.bioinfo.no/site/

Gene expression analysis software using Java.

Proper citation: J-Express (RRID:SCR_003609) Copy   

•   Source: SciCrunch Registry

http://mendel.stanford.edu/sidowlab/downloads/quest/

A Kernel Density Estimator-based package for analysis of massively parallel sequencing data from chromatin immunoprecipitation (ChIP-seq) experiments.

Proper citation: Quantitative Enrichment of Sequence Tags (RRID:SCR_004065) Copy   

•   Source: SciCrunch Registry

http://www.brl.bcm.tmc.edu/pash/pashDownload.rhtml

Performs sequence comparison and read mapping and can be employed as a module within diverse configurable analysis pipelines, including ChIP-Seq and methylome mapping by whole-genome bisulfite sequencing.

Proper citation: Pash 3.0 (RRID:SCR_004078) Copy   

•   Source: SciCrunch Registry

http://epigraph.mpi-inf.mpg.de/WebGRAPH/

A software for genome and epigenome analysis., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: EpiGRAPH (RRID:SCR_004326) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/insertionmapper/

A pipeline tool for the identification of targeted sequences from multidimensional high throughput sequencing data. It consists of four independently working modules: Data Preprocessing, Database Modeling, Dimension Deconvolution and Element Mapping. This pipeline tool is applicable to scenarios requiring analysis of the tremendous output of short reads produced in NGS sequencing experiments of targeted genome sequences.

Proper citation: InsertionMapper (RRID:SCR_004163) Copy   

•   Source: SciCrunch Registry

https://bcbio-nextgen.readthedocs.org/en/latest/

A python toolkit providing best-practice pipelines for fully automated high throughput sequencing analysis.

Proper citation: bcbio-nextgen (RRID:SCR_004316) Copy   

•   Source: SciCrunch Registry