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https://github.com/HingeAssembler/HINGE

Software application for long read genome assembly based on hinging. Used in long-read sequencing technologies in genome assemblies to achieve optimal repeat resolution.

Proper citation: Hinge (RRID:SCR_016135) Copy   

•   Source: SciCrunch Registry
  

https://github.com/soedinglab/hh-suite

Software package for sensitive protein sequence searching based on the pairwise alignment of hidden Markov models (HMMs). Used for sequence-based protein function and structure prediction what depends on sequence-search sensitivity and accuracy of the resulting sequence alignments.

Proper citation: HH-suite (RRID:SCR_016133) Copy   

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https://github.com/ruanjue/smartdenovo

Software tool as de novo assembler for PacBio and Oxford Nanopore data. It produces assembly from all-vs-all raw read alignments without error correction stage. Allows to read overlapping, rescue missing overlaps, identify low-quality regions and chimaera and produce better consensus.

Proper citation: SMARTdenovo (RRID:SCR_017622) Copy   

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https://www.rdocumentation.org/packages/pheatmap/versions/0.2/topics/pheatmap

Software tool as a function in R to draw clustered heatmaps for better control over graphical parameters.

Proper citation: pheatmap (RRID:SCR_016418) Copy   

•   Source: SciCrunch Registry
  

https://github.com/mahmoudibrahim/JAMM

Software tool as peak finder for joint analysis of NGS replicates. Used for peak finding in next generation sequencing broad and narrow datasets like ChIP-Seq, ATAC-Seq, DNase-Seq. Can integrate information from biological replicates and assign peak boundaries accurately.

Proper citation: JAMM (RRID:SCR_017049) Copy   

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http://www.cbs.dtu.dk/services/NetPhos/

Web tool as artificial neural network method that predicts phosphorylation sites in independent sequences. Web application based on determination of activity of protein kinases using in vitro assays with either naturally occurring peptides or synthetic peptides. NetPhos 3.1 server predicts serine, threonine or tyrosine phosphorylation sites in eukaryotic proteins using ensembles of neural networks. Both generic and kinase specific predictions are performed. Generic predictions are identical to predictions performed by NetPhos 2.0. Kinase specific predictions are identical to predictions by NetPhosK 1.0. NetPhos 3.1 is available as stand-alone software package.

Proper citation: NetPhos (RRID:SCR_017975) Copy   

•   Source: SciCrunch Registry
  

http://bioinformatics.uni-muenster.de/tools/nanopipe2

Web tool for analysis of MinION (ONT) long sequencing reads. Used for analysis of reads generated by the Oxford Nanopore sequencing devices. Provides alignments to any target of interest, alignment statistics and information about polymorphisms.

Proper citation: NanoPipe (RRID:SCR_016852) Copy   

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http://deweylab.biostat.wisc.edu/detonate/

Software tool to evaluate de novo transcriptome assemblies from RNA-Seq data. Consists of RSEM-EVAL and REF-EVAL packages. RSEM-EVAL is reference-free evaluation method. REF-EVAL is reference based and can be used to compare sets of any kinds of genomic sequences.

Proper citation: DETONATE (RRID:SCR_017035) Copy   

•   Source: SciCrunch Registry
  

https://github.com/xavierdidelot/clonalorigin

Software package for comparative analysis of the sequences of a sample of bacterial genomes in order to reconstruct the recombination events that have taken place in their ancestry.

Proper citation: ClonalOrigin (RRID:SCR_016061) Copy   

•   Source: SciCrunch Registry
  

http://srv00.recas.ba.infn.it/atlas/index.html

Comprehensive database of A-to-I RNA Editing Events. Atlas of A-to-I RNA editing events in human and other organisms. Collection of A-to-I events in body sites of healthy individuals from GTEx project. RNA Editing sites can be searched by genomic region, gene name and other relevant features as tissue of origin. Query results are shown in sortable and downloadable tables in which main characteristics of individual RNA editing events are reported. RNA-Seq and DNA-Seq coverage per site as well as RNA editing levels are provided.

Proper citation: REDIportal (RRID:SCR_018490) Copy   

•   Source: SciCrunch Registry
  

https://github.com/zhanxw/MB-GAN

Software tool as deep learning simulation framework for simulating realistic microbiome data. Can automatically learn from given microbial abundances and compute simulated abundances that are indistinguishable from it.

Proper citation: MB-GAN (RRID:SCR_019289) Copy   

•   Source: SciCrunch Registry
  

http://www.bioconductor.org/packages/release/bioc/html/iontree.html

Software package that provides utility functions to manage and analyse MS2/MS3 fragmentation data from ion trap mass spectrometry. It was designed for high throughput metabolomics data with many biological samples and a large numer of ion trees collected. Tests have been done with data from low-resolution mass spectrometry but could be readily extended to precursor ion based fragmentation data from high resoultion mass spectrometry.

Proper citation: iontree (RRID:SCR_002813) Copy   

•   Source: SciCrunch Registry
  

http://www.cprofiler.org/

Web tool for discovery and visualization of differences in amino acid composition. Two samples of amino acid sequences serve as input and a bar chart composed of twenty data points is output.

Proper citation: Composition Profiler (RRID:SCR_014630) Copy   

•   Source: SciCrunch Registry
  

http://www.cazy.org

Database that describes the families of structurally-related catalytic and carbohydrate-binding modules (or functional domains) of enzymes that degrade, modify, or create glycosidic bonds. This specialist database is dedicated to the display and analysis of genomic, structural and biochemical information on Carbohydrate-Active Enzymes (CAZymes). CAZy data are accessible either by browsing sequence-based families or by browsing the content of genomes in carbohydrate-active enzymes. New genomes are added regularly shortly after they appear in the daily releases of GenBank. New families are created based on published evidence for the activity of at least one member of the family and all families are regularly updated, both in content and in description. An original aspect of the CAZy database is its attempt to cover all carbohydrate-active enzymes across organisms and across subfields of glycosciences. One can search for CAZY Family pages using the Protein Accession (Genpept Accession, Uniprot Accession or PDB ID), Cazy family name or EC number. In addition, genomes can be searched using the NCBI TaxID. This search can be complemented by Google-based searches on the CAZy site.

Proper citation: CAZy- Carbohydrate Active Enzyme (RRID:SCR_012909) Copy   

•   Source: SciCrunch Registry
  

http://www.cbs.dtu.dk/services/ProP/

Web application which predicts arginine and lysine propeptide cleavage sites in eukaryotic protein sequences using an ensemble of neural networks. Furin-specific prediction is the default. It is also possible to perform a general proprotein convertase prediction.

Proper citation: ProP Server (RRID:SCR_014936) Copy   

•   Source: SciCrunch Registry
  

http://www.ebi.ac.uk/Tools/psa/genewise/

Gene alignment tool from the EBI which predicts gene structure using similar protein sequences. See also the associated GenomeWise tool.

Proper citation: GeneWise (RRID:SCR_015054) Copy   

•   Source: SciCrunch Registry
  

http://fantom.gsc.riken.jp/4/

The FANTOM consortium is an international collaborative research project initiated and organized by the RIKEN Omics Science Center. In earlier FANTOM efforts we cloned and annotated 103,000 full-length cDNAs from mouse and distributed them to researchers throughout the world. FANTOM1-3 focused on identifying the transcribed components of mammalian cells. This work improved estimates of the total number of genes and their alternative transcript isoforms in both human and mouse, expanded gene families, and revealed that a large fraction of the transcriptome is non-coding. In addition, with the development of Cap Analysis of Gene Expression (CAGE) FANTOM3 could map a large fraction of transcription start sites and revise our models of promoter structure. This updated web resource provides the previous FANTOM results mapped to current genome builds and presents the results of FANTOM4. In FANTOM4 the focus has changed to understanding how these components work together in the context of a biological network. Using deepCAGE (deep sequencing with CAGE) we monitored the dynamics of transcription start site (TSS) usage during a time course of monocytic differentiation in the acute myeloid leukemia cell line THP-1. This allowed us to identify active promoters, monitor their relative expression and define relevant regions for carrying out transcription factor binding site predictions. Computational methods were then used to build a network model of gene expression in this leukemia and the transcription factors key to its regulation. This work gives the first picture of the wiring between genes involved in acute myeloid leukemia and provides a strategy for identifying key factors that determine cell fates. In addition to the network, FANTOM4 data was used in two additional analyses. The first identified a novel class of short RNAs associated with transcription start sites and the second focused on the role of repetitive element expression in the transcriptome. TOOLS *Genome Browser: graphical display of genomic features, such as promoters, exon structures, H3K9 acetylation, transcription factors positioning on the genome, coupled with gene and promoter activities. *EdgeExpressDB: regulatory interactions, such as transcriptional regulation, post-transcriptional silencing with miRNA, and PPI, coupled with gene and promoter activities. *SwissRegulon: FANTOM4 TF regulation is predicted using Motif Activity Response Analysis (MARA) developed by Erik van Nimwegen at Biozentrum. Follow the link to carry out MARA on your own dataset. *Custom Tracks on the UCSC Genome Browser: FANTOM4 tracks on the UCSC Genome Browser Database. *The RIKEN integrated database of mammals: Integration of FANTOM4 data with other mammalian resources, in particular, produced by RIKEN.

Proper citation: FANTOM DB (RRID:SCR_002678) Copy   

•   Source: SciCrunch Registry
  

https://github.com/eduardporta/e-Driver

Software tool to identify cancer driver genes based on linear annotations of biological regions such as protein domains.Uses information on three-dimensional structures of mutated proteins to identify specific structural features. Then algorithm analyzes whether these features are enriched in cancer somatic mutations and are candidate driver genes.

Proper citation: e-Driver (RRID:SCR_002674) Copy   

•   Source: SciCrunch Registry
  

http://www.cs.ucr.edu/~yyang027/mrfseq.htm

Algorithm based on a Markov random field (MRF) model that uses additional gene coexpression data to enhance differential gene expression prediction power. It is able to call differentially expressed (DE) genes but also assign confidence scores to each inferred DE gene.

Proper citation: MRFSEQ (RRID:SCR_002972) Copy   

•   Source: SciCrunch Registry
  

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

THIS RESOURCE IS NO LONGER IN SERVICE.Documented on January 4,2023. IgBLAST was developed at NCBI to facilitate analysis of immunoglobulin V region sequences in GenBank. In addition to performing a regular BLAST search, IgBLAST has several additional functions: - Reports the germline V, D and J gene matches to the query sequence. - Annotates the immunoglobulin domains (FWR1 through FWR3). - Matches the returned hits (for databases other than germline genes) to the closest germline V genes, making it easier to identify related sequences. - Reveals the V(D)J junction details such as nucleotide homology between the ends of V(D)J segments and N nucleotide insertions. D and J gene reporting is only for nucleotide sequence search and requires a stretch of five or more nucleotide identity between the query and D or J genes. Sponsors: This resource is supported by the National Center for Biotechnology Information, a division of the U.S. National Library of Medicine.

Proper citation: IgBLAST (RRID:SCR_002873) Copy   

•   Source: SciCrunch Registry