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http://www.thegpm.org/tandem/

Software tool that can match tandem mass spectra with peptide sequences, in process known as protein identification. Database search engine for matching tandem mass spectra with protein sequences. Command line tool for matching tandem mass spectra with peptide sequences.

Proper citation: X!Tandem (RRID:SCR_015645) Copy   

•   Source: SciCrunch Registry

https://jasp-stats.org/

Statistics software that performs common frequentist analyses and Bayesian analyses. It conducts ANOVA, linear regression, and correlation, among other statistical tests.

Proper citation: JASP (RRID:SCR_015823) Copy   

•   Source: SciCrunch Registry

http://apps.cytoscape.org/apps/mcode

Software that clusters a given network based on topology to find densely connected regions. It can be used to find protein complexes and parts of pathways in protein-protein interaction networks or protein families in protein similarity networks.

Proper citation: MCODE (RRID:SCR_015828) Copy   

•   Source: SciCrunch Registry

https://www.github.com/arq5x/poretools

Software toolkit for analyzing nanopore sequence data.

Proper citation: Poretools (RRID:SCR_015879) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/eeglab/

Interactive Matlab toolbox for processing continuous and event-related EEG, MEG and other electrophysiological data incorporating independent component analysis (ICA), time/frequency analysis, artifact rejection, event-related statistics, and several useful modes of visualization of the averaged and single-trial data. First developed on Matlab 5.3 under Linux, EEGLAB runs on Matlab v5 and higher under Linux, Unix, Windows, and Mac OS X (Matlab 7+ recommended). EEGLAB provides an interactive graphic user interface (GUI) allowing users to flexibly and interactively process their high-density EEG and other dynamic brain data using independent component analysis (ICA) and/or time/frequency analysis (TFA), as well as standard averaging methods. EEGLAB also incorporates extensive tutorial and help windows, plus a command history function that eases users'' transition from GUI-based data exploration to building and running batch or custom data analysis scripts. EEGLAB offers a wealth of methods for visualizing and modeling event-related brain dynamics, both at the level of individual EEGLAB ''datasets'' and/or across a collection of datasets brought together in an EEGLAB ''studyset.'' For experienced Matlab users, EEGLAB offers a structured programming environment for storing, accessing, measuring, manipulating and visualizing event-related EEG data. For creative research programmers and methods developers, EEGLAB offers an extensible, open-source platform through which they can share new methods with the world research community by publishing EEGLAB ''plug-in'' functions that appear automatically in the EEGLAB menu of users who download them. For example, novel EEGLAB plug-ins might be built and released to ''pick peaks'' in ERP or time/frequency results, or to perform specialized import/export, data visualization, or inverse source modeling of EEG, MEG, and/or ECOG data. EEGLAB Features * Graphic user interface * Multiformat data importing * High-density data scrolling * Defined EEG data structure * Open source plug-in facility * Interactive plotting functions * Semi-automated artifact removal * ICA & time/frequency transforms * Many advanced plug-in toolboxes * Event & channel location handling * Forward/inverse head/source modeling

Proper citation: EEGLAB (RRID:SCR_007292) 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://www.gelifesciences.com/webapp/wcs/stores/servlet/catalog/en/GELifeSciences-us/products/AlternativeProductStructure_16016/29000605

Software for automatic general image analysis. It provides fully automatic analysis of 1-D gels including lane creation, background subtraction, band detection, molecular weight calibration, quantity calibration, and normalization. Editing tools are provided for cropping, rotating, and filtering images., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: ImageQuant (RRID:SCR_014246) Copy   

•   Source: SciCrunch Registry

https://pathcore.bsd.uchicago.edu/Downloads/HTRC_ImageScUG.pdf

Slide image modification software that allows the user to adjust the magnification, compare slides, pan and zoom, annotate specific areas, and perform image analysis of digital slides. Users can create macros and algorithms to automate analysis and create plots, respectively., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: ImageScope (RRID:SCR_014311) Copy   

•   Source: SciCrunch Registry

https://www.embl-hamburg.de/biosaxs/software.html

Software toolkit for small-angle scattering data analysis from biological macromolecules.

Proper citation: ATSAS (RRID:SCR_015648) Copy   

•   Source: SciCrunch Registry

http://autodock.scripps.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 23,2023.Software for automated docking analysis to precalculate the set of grids describing the target protein. It is a part of automated molecular modeling simulation software AutoDock.

Proper citation: Autogrid (RRID:SCR_015982) Copy   

•   Source: SciCrunch Registry

https://www.schrodinger.com/epik

Software program for pKa prediction and protonation state generation for drug like molecules.

Proper citation: Epik (RRID:SCR_016745) Copy   

•   Source: SciCrunch Registry

http://www.scandb.org/newinterface/about.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 17, 2022. A large-scale database of genetics and genomics data associated to a web-interface and a set of methods and algorithms that can be used for mining the data in it. The database contains two categories of single nucleotide polymorphism (SNP) annotations: # Physical-based annotation where SNPs are categorized according to their position relative to genes (intronic, inter-genic, etc.) and according to linkage disequilibrium (LD) patterns (an inter-genic SNP can be annotated to a gene if it is in LD with variation in the gene). # Functional annotation where SNPs are classified according to their effects on expression levels, i.e. whether they are expression quantitative trait loci (eQTLs) for that gene. SCAN can be utilized in several ways including: (i) queries of the SNP and gene databases; (ii) analysis using the attached tools and algorithms; (iii) downloading files with SNP annotation for various GWA platforms. . eQTL files and reported GWAS from NHGRI may be downloaded., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: SCAN (RRID:SCR_005185) 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

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

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