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http://support.illumina.com/sequencing/sequencing_software/casava.html

Software package that creates genomic builds, calls SNPs, detects indels, and counts reads from data generated from one or more sequencing runs. In addition, CASAVA automatically generates a range of statistics, such as mean depth and percentage chromosome coverage, to enable comparison with previous builds or other samples. CASAVA analyzes sequencing reads in three stages: * FASTQ file generation and demultiplexing * Alignment to a reference genome * Variant detection and counting

Proper citation: CASAVA (RRID:SCR_001802) Copy   

•   Source: SciCrunch Registry

http://tcoffee.crg.cat/apps/tcoffee/do:regular

A multiple sequence alignment server which can align Protein, DNA and RNA sequences.

Proper citation: T-Coffee (RRID:SCR_011818) Copy   

•   Source: SciCrunch Registry

http://probcons.stanford.edu/

Efficient protein multiple sequence alignment program, which has demonstrated a statistically significant improvement in accuracy compared to several leading alignment tools.

Proper citation: ProbCons (RRID:SCR_011813) Copy   

•   Source: SciCrunch Registry

http://genevenn.sourceforge.net/

A web application creating Venn diagrams from two or three gene lists.

Proper citation: GeneVenn (RRID:SCR_012117) Copy   

•   Source: SciCrunch Registry

http://blast.ncbi.nlm.nih.gov/Blast.cgi?PROGRAM=tblastn&PAGE_TYPE=BlastSearch&LINK_LOC=blasthome

Tool to search translated nucleotide databases using a protein query.

Proper citation: TBLASTN (RRID:SCR_011822) Copy   

•   Source: SciCrunch Registry

http://nhjy.hzau.edu.cn/kech/swxxx/jakj/dianzi/Bioinf6/GeneFinding/GeneFinding2.htm

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 10,2020. Data analysis service for Hidden Markov Model (HMM)-based gene structure prediction (multiple genes, both chains).

Proper citation: FGENESH (RRID:SCR_011928) Copy   

•   Source: SciCrunch Registry

http://gpcr.biocomp.unibo.it/bacello/

A predictor for the subcellular localization of proteins in eukaryotes that is based on a decision tree of several support vector machines (SVMs). It classifies up to four localizations for Fungi and Metazoan proteins and five localizations for Plant ones. BaCelLo's predictions are balanced among different classes and all the localizations are considered as equiprobable.

Proper citation: BaCelLo (RRID:SCR_011965) Copy   

•   Source: SciCrunch Registry

http://Mar2008.archive.ensembl.org

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 17,2022. Genome databases for vertebrates and other eukaryotic species. Analysis and annotation maintained on current data.Distribution of analysis to other bioinformatics laboratories. Ensembl concentrates on vertebrate genomes, but other groups have adapted system for use with plant and fungal genomes (see Powered by Ensembl list on website).

Proper citation: Ensembl Genome Browser (RRID:SCR_013367) Copy   

•   Source: SciCrunch Registry

https://www.webofscience.com/wos/woscc/advanced-search

Database of bibliographic citations of multidisciplinary areas that covers various journals of medical, scientific, and social sciences including humanities.Publisher independent global citation database.

Proper citation: Web of Science (RRID:SCR_022706) Copy   

•   Source: SciCrunch Registry

http://www.scipy.org/

A Python-based environment of open-source software for mathematics, science, and engineering. The core packages of SciPy include: NumPy, a base N-dimensional array package; SciPy Library, a fundamental library for scientific computing; and IPython, an enhanced interactive console.

Proper citation: SciPy (RRID:SCR_008058) Copy   

•   Source: SciCrunch Registry

http://www.sas.com

Software platform to explore, analyze and visualize data. SAS 9.4 is part of SAS Platform. Standardized data governance and management from statistical software company SAS.

Proper citation: Statistical Analysis System (RRID:SCR_008567) Copy   

•   Source: SciCrunch Registry

http://srv00.recas.ba.infn.it/ASPicDB/

A database to access reliable annotations of the alternative splicing pattern of human genes, obtained by ASPic algorithm (Castrignano et al. 2006), and to the functional annotation of predicted isoforms. Users may select and extract specific sets of data related to genes, transcripts and introns fulfilling a combination of user-defined criteria. Several tabular and graphical views of the results are presented, providing a comprehensive assessment of the functional implication of alternative splicing in the gene set under investigation. ASPicDB also includes information on tissue-specific splicing patterns of normal and cancer cells, based on available EST data and their library source annotation.

Proper citation: ASPicDB (RRID:SCR_002102) Copy   

•   Source: SciCrunch Registry

http://www-stat.stanford.edu/~tibs/SAM/

Software for genomic expression data mining using a statistical technique for finding significant genes in a set of microarray experiments.

Proper citation: SAM (RRID:SCR_010951) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.vub.ac.be/databases/databases.html

Downloadable data set designed to assess the performance of both multiple and pairwise (protein) sequence alignment algorithms, and is extremely easy to use. Currently, the database contains 2 sets, each consisting of a number of subsets with related sequences. It''s main features are: * Covers the entire known fold space (SCOP classification), with subsets provided by the ASTRAL compendium * All structures have high quality, with 100% resolved residues * Structure alignments have been derived carefully, using both SOFI and CE, and Relaxed Transitive Alignment * At most 25 sequences in each subset to avoid overrepresentation of large folds* Automated running, archiving and scoring of programs through a few Perl scripts The Twilight Zone set is divided into sequence groups that each represent a SCOP fold. All sequences within a group share a pairwise Blast e-value of at least 1, for a theoretical database size of 100 million residues. Sequence similarity is thus very low, between 0-25% identity, and a (traceable) common evolutionary origin cannot be established between most pairs even though their structures are (distantly) similar. This set therefore represents the worst case scenario for sequence alignment, which unfortunately is also the most frequent one, as most related sequences share less than 25% identity. The Superfamilies set consists of groups that each represent a SCOP superfamily, and therefore contain sequences with a (putative) common evolutionary origin. However, they share at most 50% identity, which is still challenging for any sequence alignment algorithm. Frequently, alignments are performed to establish whether or not sequences are related. To benchmark this, a second version of both the Twilight Zone and the Superfamilies set is provided, in which to each alignment problem a number of false positives, i.e. sequences not related to the original set, are added. Database specifications: * Current version: 1.65 (concurrent with PDB, SCOP and ASTRAL) * Twilight Zone set (with false positives): 209 groups, 1740 (3280) sequences, 10667 (44056) related pairs * Superfamilies set (with false positives): 425 groups, 3280 (6526) sequences, 19092 (79095) related pairs

Proper citation: SABmark (RRID:SCR_011817) Copy   

•   Source: SciCrunch Registry

https://github.com/ElsevierSoftwareX/SOFTX-D-15-00082

Software PCA-based toolkit for compression and analysis of molecular simulation data. Used for compression and analysis of molecular dynamics (MD) simulation data.

Proper citation: pyPCcazip (RRID:SCR_024423) Copy   

•   Source: SciCrunch Registry

http://www.stata.com

Software package for statistical analysis and presentation of graphics. Statistical software for data science.

Proper citation: Stata (RRID:SCR_012763) Copy   

•   Source: SciCrunch Registry