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https://imjoy.io

Software tool as plugin powered hybrid computing platform for deploying deep learning applications such as advanced image analysis tools. Runs on mobile and desktop environment cross different operating systems, can run in the browser, localhost, remote and cloud servers.

Proper citation: ImJoy (RRID:SCR_020935) Copy   

•   Source: SciCrunch Registry

http://ms-utils.org

Open source software suite for mass spectrometry based proteomics. Software repository and collection of free software for analysis of mass spectrometry data. Software and code snippets for visualization and analysis of mass spectrometry data with emphasis on automated methods for proteomics and protein analysis.

Proper citation: ms-utils.org (RRID:SCR_019810) Copy   

•   Source: SciCrunch Registry

http://srna-workbench.cmp.uea.ac.uk

Software package for analysing small RNA data. Software suite of tools for analyzing miRNAs and sRNAs. Performs analysis of single or multiple sample small RNA datasets from both plants and animals.

Proper citation: UEA sRNA Workbench (RRID:SCR_020947) Copy   

•   Source: SciCrunch Registry

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

Software R package for statistical analysis of phenotypic data.Tool kit for standardized analysis of high throughput phenotypic data.

Proper citation: PhenStat (RRID:SCR_021317) Copy   

•   Source: SciCrunch Registry

http://cran.r-project.org/web/packages/mlgt/index.html

Software for processing and analysis of high throughput (Roche 454) sequences generated from multiple loci and multiple biological samples. Sequences are assigned to their locus and sample of origin, aligned and trimmed. Where possible, genotypes are called and variants mapped to known alleles.

Proper citation: mlgt (RRID:SCR_001211) Copy   

•   Source: SciCrunch Registry

http://soap.genomics.org.cn/

Software package that provides full solution to next generation sequencing data analysis consisting of an alignment tool (SOAPaligner/soap2), a re-sequencing consensus sequence builder (SOAPsnp), an indel finder ( SOAPindel ), a structural variation scanner ( SOAPsv ), a de novo short reads assembler ( SOAPdenovo ), and a GPU-accelerated alignment tool for aligning short reads with a reference sequence. (SOAP3/GPU)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: SOAP (RRID:SCR_000689) Copy   

•   Source: SciCrunch Registry

http://idash.ucsd.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 6, 2023. National Center for Biomedical Computing (NCBC) that develops new algorithms, opensource tools, computational infrastructure, and services for biomedical and behavioral researchers nationwide to promote the secure sharing and consuming of biomedical and behavioral resources (software, data, and computing systems) with iDASH collaborators. The center addresses fundamental challenges to research progress by providing a secure, privacypreserving environment in which researchers can analyze genomic, transcriptomic, clinical, behavioral, and social data relevant to health. Three driving biological projects in iDASH (Molecular Phenotyping of Kawasaki Disease, Post-Marketing Surveillance of Hematologic Medications, and Individualized Intervention to Enhance Physical Activity) span the molecular-individualpopulation spectrum, and they will motivate, inform, and support tool development. iDASH will collaborate with other NCBCs and will disseminate tools via annual workshops, presentations at major conferences, and scientific publications.

Proper citation: iDASH (RRID:SCR_003524) Copy   

•   Source: SciCrunch Registry

https://github.com/gt1/biobambam

Software tools for read pair collation based algorithms on BAM files including * bamcollate2: reads BAM and writes BAM reordered such that alignment or collated by query name * bammarkduplicates: reads BAM and writes BAM with duplicate alignments marked using the BAM flags field * bammaskflags: reads BAM and writes BAM while masking (removing) bits from the flags column * bamrecompress: reads BAM and writes BAM with a defined compression setting. This tool is capable of multi-threading. * bamsort: reads BAM and writes BAM resorted by coordinates or query name * bamtofastq: reads BAM and writes FastQ; output can be collated or uncollated by query name

Proper citation: biobambam (RRID:SCR_003308) Copy   

•   Source: SciCrunch Registry

http://phenoscape.org/

Project to create a scalable infrastructure that enables linking phenotypes across different fields of biology by the semantic similarity of their descriptions.

Proper citation: Phenoscape (RRID:SCR_003799) Copy   

•   Source: SciCrunch Registry

http://hannonlab.cshl.edu/fastx_toolkit/

Software tool as collection of command line tools for Short-Reads FASTA/FASTQ files preprocessing.

Proper citation: FASTX-Toolkit (RRID:SCR_005534) Copy   

•   Source: SciCrunch Registry

https://github.com/najoshi/sickle

Software tool for windowed adaptive trimming for fastq files using quality. Supports quality values like Illumina, Solexa, and Sanger. Takes the quality values and slides a window across them whose length is 0.1 times the length of the read.

Proper citation: Sickle (RRID:SCR_006800) Copy   

•   Source: SciCrunch Registry

http://code.google.com/p/seqtrace/

A software application for viewing and processing DNA sequencing chromatograms (trace files) that makes it easy to quickly generate high-quality finished sequences from a large number of trace files. SeqTrace can automatically identify, align, and compute consensus sequences from matching forward and reverse traces, filter low-quality base calls, and perform end trimming of finished sequences. The finished DNA sequences can then be exported to common sequence file formats, such as FASTA. SeqTrace also includes a full-featured trace file viewer and editor. You can view your sequencing chromatograms at a variety of scales and zoom levels, simultaneously view matching forward and reverse traces, edit the called bases, and export individual DNA sequences as well as forward/reverse alignments. SeqTrace supports popular trace file formats, including ABIF, SCF, and ZTR.

Proper citation: SeqTrace (RRID:SCR_005580) Copy   

•   Source: SciCrunch Registry

http://hollywood.mit.edu/burgelab/rescue-ese/

Specific short oligonucleotide sequences that enhance pre-mRNA splicing when present in exons, termed exonic splicing enhancers (ESEs), play important roles in constitutive and alternative splicing (ESE References). A hybrid computational/experimental method, RESCUE-ESE, was recently developed for identifying sequences with ESE activity. In this approach, specific hexanucleotide sequences are identified as candidate ESEs on the basis that they have both significantly higher frequency of occurrence in exons than in introns and also significantly higher frequency in exons with weak (non-consensus) splice sites than in exons with strong (consensus) splice sites. Representative hexamers from ten different classes of candidate ESEs, together with 6 or 7 bases of flanking sequence context on each side, were introduced into a weak (poorly spliced) exon in a splicing reporter construct. These reporter minigenes were then transfected into cultured cells, where they are transcribed and spliced, and the relative level of inclusion of the test exon was assayed by quantitative (radio-labeled) RT-PCR. Point mutants of these sequences were also analyzed to confirm the precise motifs responsible for ESE activity. The RESCUE-ESE approach identified 238 hexamers as candidate ESEs using a large database of human genes of known exon-intron structure containing over 30,000 nonredudant exons. In more recent analyses by Yeo et al., the RESCUE-ESE approach was utilized to predict hexamers as candidate ESEs in other vertebrate genes, namely, Fugu rubipes, Zebrafish and Mouse. This allows the identification of motifs that are conserved in vertebrates. This web server allows a sequence to be checked for presence of these candidate ESE hexamers.

Proper citation: RESCUE-ESE (RRID:SCR_008496) Copy   

•   Source: SciCrunch Registry

http://www.usadellab.org/cms/index.php?page=trimmomatic

Software Java pipeline for trimming tasks for Illumina paired end and single ended data. Flexible Trimmer for Illumina Sequence Data. Pair aware preprocessing tool optimized for Illumina next generation sequencing data. Includes several processing steps for read trimming and filtering. Operating systems Unix/Linux, Mac OS, Windows.

Proper citation: Trimmomatic (RRID:SCR_011848) Copy   

•   Source: SciCrunch Registry

http://polbase.neb.com/

Repository of biochemical, genetic, and structural information about DNA Polymerases. Polbase is designed to compile detailed results of polymerase experimentation, presenting them in a dynamic view to inform further research. After validation, results from references are displayed in context with relevant experimental details and are always traceable to their source publication. Polbase is connected to other resources, including PubMed, UniProt and the RCSB Protein Data Bank, to provide multi-faceted views of polymerase knowledge. In addition to a simple web interface, Polbase data is exposed for custom analysis by external software.

Proper citation: Polbase (RRID:SCR_006107) Copy   

•   Source: SciCrunch Registry

http://www.umd.be/BRCA1/

The UMD-BRCA1/BRCA2 databases have been set up in a joined national effort through the network of 16 diagnostic laboratories to provide up-to-date information about mutations of the BRCA1 and BRCA2 genes identified in patients with breast and/or ovarian cancer. These databases currently contain published and unpublished information about the BRCA1/BRCA2 mutations reported in French diagnostic laboratories. This database includes 28 references and 5530 mutations (1440 different mutations and 786 protein variants) The databases of BRCA1 and BRCA2 mutations were built using the Universal Mutation Database tool. For each mutation, information is provided at several levels: * at the gene level: exon and codon number, wild type and mutant codon, mutation event, mutation name and, * at the protein level: wild type and mutant amino acid, binding domain, affected domain. If you want to submit a mutation, please contact R. Lidereau., S. Caputo. or E. Rouleau.

Proper citation: UMD-BRCA1/ BRCA2 databases (RRID:SCR_006128) Copy   

•   Source: SciCrunch Registry

https://github.com/stamatak/standard-RAxML

Software program for phylogenetic analyses of large datasets under maximum likelihood.

Proper citation: RAxML (RRID:SCR_006086) Copy   

•   Source: SciCrunch Registry

http://ogeedb.embl.de/#summary

Online GEne Essentiality database containing genes that were tested experimentally for essentiality and their features; it also provides a set of tools to systematically explore and analyze these data. The main purpose of this project is to better understand gene essentiality by facilitating the comparisons of the differences and similarities between essential and non-essential genes. This is achieved by collecting not only experimentally tested essential and non-essential genes, but also associated gene features such as expression profiles, duplication status, conservation across species, evolutionary origins and involvement in embryonic development. We focus on large-scale experiments and complement our data with text-mining results. Genes are organized into data sets according to their sources. Genes with variable essentiality status across data sets are tagged as conditionally essential, highlighting the complex interplay between gene functions and environments. Linked tools allow the user to compare gene essentiality among different gene groups, or compare features of essential genes to non-essential genes, and visualize the results. Why is it different from existing databases? * we included both essential and non-essential genes so that we could better understand the gene essentiality by comparing the similarities and differences between the two gene sets; * we compiled a list of features for each gene, including whether they are duplicates or involved in development, the number of other homologous genes in the same genome, as well as their earliest expression stages during development. These features are keys to understand the essentiality of genes; * we also provide a set of tools to explore our data and visualize the results. For example, users can simply divide genes into two groups according to whether they are duplicates, calculate the proportion of essential genes (PE%) in each group and then visualize the results in a bar plot; or they can classify genes into multiple groups according to their earliest expression stages during evolution, compare the essentiality of genes that were expressed earlier with those were latter, and plot the results in a line chart.

Proper citation: OGEE - Online GEne Essentiality database (RRID:SCR_006080) Copy   

•   Source: SciCrunch Registry

http://athina.biol.uoa.gr/bioinformatics/PRED-GPCR/

A prediction tool for GPCR Family Classification from sequence alone based on a probabilistic method that uses family-specific profile Hidden Markov Models. The PRED-GPCR system is based on a probabilistic method that uses family specific profile HMMs in order to determine to which GPCR family a query sequence belongs or resembles. The approach proposed in this method exploits the descriptive power of profile HMMs along with an exhaustive discrimination assessment method to select only highly selective and sensitive profiles, for each family. The collection of these profiles constitutes a signature library, which is scanned, for significant matches with a given query sequence. The output report for a query sequence consists of two sections: * A ranked list of the profile HMM matches, below the selected individual motif E-value cutoff, along with their corresponding family. * A ranked list of the Combined P-values, E-values as well as the number of profiles matched for each family. To cross-evaluate your results you can browse through Swiss-Prot, Trembl, Pfam and Prosite family related entries.

Proper citation: PRED-GPCR (RRID:SCR_006196) Copy   

•   Source: SciCrunch Registry

http://www.hudsen.org/

Forum for researchers in human developmental biology and related fields to meet and establish links.

Proper citation: HUDSEN (RRID:SCR_006324) Copy   

•   Source: SciCrunch Registry