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http://cajadb.neuro.ufrn.br

Software application as an integrated web resource of marmoset biological data. Used to find genomic, expression and alternative splicing data to facilitate the study of animal model for neuropsychiatric and social behavior research and to support biological analyses such as functional (ontology) enrichment analysis and protein-protein-network.

Proper citation: CajaDB (RRID:SCR_016506) Copy   

•   Source: SciCrunch Registry

https://www.genome.jp/tools/dinies/

Web server for predicting unknown drug-target interaction networks from various types of biological data in the framework of supervised network inference.

Proper citation: DINIES (RRID:SCR_016505) Copy   

•   Source: SciCrunch Registry

http://www.compbio.dundee.ac.uk/jpred/

Software tool for protein secondary structure prediction from the amino acid sequence by the JNet algorithm. Makes also predictions on Solvent Accessibility and Coiled-coil regions.

Proper citation: Jpred (RRID:SCR_016504) Copy   

•   Source: SciCrunch Registry

http://bioinf.bio.uth.gr/nat-ncs2

Web server for the detection and evolutionary classification of prokaryotic and eukaryotic nucleobase-cation symporters of the NAT/NCS2 family. Used to scan, identify and evolutionary classify NAT/NCS2 nucleobase transporter proteins.

Proper citation: NAT/NCS2 Hound (RRID:SCR_016473) Copy   

•   Source: SciCrunch Registry

https://imaps.genialis.com/iclip

Web server for analysis of high-resolution sequencing data. It can be used with all variants of CLIP,as well as with methods that interrogate RNA or DNA methylation, RNA processing, RNA structure or protein-DNA interactions.

Proper citation: iMaps (RRID:SCR_016705) Copy   

•   Source: SciCrunch Registry

https://github.com/tomazc/iCount

Software Python package for protein-RNA interaction analysis. Used for analysis of protein-RNA interactions with iCLIP sequencing data and RNA maps.

Proper citation: iCount (RRID:SCR_016712) Copy   

•   Source: SciCrunch Registry

http://projects.biotec.tu-dresden.de/metapocket/

Software tool to identify pockets on protein surface to predict ligand-binding sites.

Proper citation: metaPocket (RRID:SCR_016653) Copy   

•   Source: SciCrunch Registry

https://www.ncbi.nlm.nih.gov/Web/Newsltr/Spring04/blastlab.html

Software tool as a program within the standalone BLAST package used to cluster either protein or nucleotide sequences. Used to make non redundant sequence sets.

Proper citation: BLASTClust (RRID:SCR_016641) Copy   

•   Source: SciCrunch Registry

https://www.ncbi.nlm.nih.gov/orffinder

Software tool to search for open reading frames (ORFs) in the DNA sequence. The program returns the range of each ORF, along with its protein translation. Used to search newly sequenced DNA for potential protein encoding segments, verify predicted protein. Limited to the subrange of the query sequence up to 50 kb long.

Proper citation: Open Reading Frame Finder (RRID:SCR_016643) Copy   

•   Source: SciCrunch Registry

http://cctop.enzim.ttk.mta.hu/

Web application providing transmembrane topology prediction. Server incorporates topology information from existing experimental and computational sources using the probabilistic framework of hidden Markov model. Provides the option to precede the topology prediction with signal peptide prediction and transmembrane globular protein discrimination. Given the amino acid sequence of a putative α helical transmembrane protein, CCTOP predicts its topology i.e. localization of membrane spanning regions and orientation of segments between them.

Proper citation: CCTOP (RRID:SCR_016963) Copy   

•   Source: SciCrunch Registry

https://pharos.nih.gov/

Program to improve understanding of properties and functions of proteins that are currently unannotated within three most commonly drug protein families: targeted G-protein coupled receptors, ion channels, and protein kinases. Includes Data and Resource Generating Centers (DRGC), Knowledge Management Center (KMC), and Resource Dissemination and Outreach Center (RDOC).

Proper citation: Illuminating the Druggable Genome (RRID:SCR_016924) Copy   

•   Source: SciCrunch Registry

https://www.ccpn.ac.uk/

Project provides tools and knowledge to maximize the impact of the biological NMR studies. CCPN software facilitates data analysis and software integration. Project promotes the exchange of knowledge and provides training and best practices for the NMR community and has leading role in the development of NMR data sharing standard and coordination of NMR instrumentation proposals. Includes CCPN Data Model for macromolecular NMR and related areas, CcpNmr suite of programs like Analysis for spectrum visualization, resonance assignment and analysis, ChemBuild to create chemical structure templates in an NMR aware manner, FormatConverter for data exchange with common textual NMR formats and SpecView for swift, format independent peak and spectrum visualization.

Proper citation: Collaborative Computing Project for NMR (RRID:SCR_016983) Copy   

•   Source: SciCrunch Registry

https://ous-research.no/bioinformatics/

Core facility provides high throughput sequencing data analysis, metagenomics data analysis, proteomics data analysis, protein structure analysis, functional genomics, programming, scripting, and database or web services.

Proper citation: Rikshospitalet-Radiumhospitalet and University of Oslo Bioinformatics Core Facility (RRID:SCR_017152) Copy   

•   Source: SciCrunch Registry

http://www.biomexsolutions.co.uk/morda

Software package for molecular replacement protein structure solution using X-ray data. Includes database and set of programs for structure solution. Automatic molecular replacement pipeline.

Proper citation: MoRDa (RRID:SCR_017278) Copy   

•   Source: SciCrunch Registry

https://bioinfo3d.cs.tau.ac.il/PatchDock/

Web server for molecular docking. Performs structure prediction of protein–protein and protein–small molecule complexes. Molecular docking algorithm based on shape complementarity principles.

Proper citation: PatchDock (RRID:SCR_017589) Copy   

•   Source: SciCrunch Registry

https://github.com/santeripuranen/SuperDCA

Software tool for global direct coupling analysis of input genome alignments. Implements variant of pseudolikelihood maximization direct coupling analysis, with emphasis on optimizations that enable its use on genome scale. May be used to discover co evolving pairs of loci.Used for genome wide epistasis analysis.

Proper citation: SuperDCA (RRID:SCR_018175) Copy   

•   Source: SciCrunch Registry

http://www.vectorbase.org

Bioinformatics Resource Center for invertebrate vectors. Provides web-based resources to scientific community conducting basic and applied research on organisms considered potential agents of biowarfare or bioterrorism or causing emerging or re-emerging diseases.

Proper citation: VectorBase (RRID:SCR_005917) Copy   

•   Source: SciCrunch Registry

http://www-bionet.sscc.ru/sitex/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 19,2019. Analyzing protein structure projection on exon-intron structure of corresponding gene through years led to several fundamental conclusions about structural and functional organization of the protein. According to these results we decided to map the protein functional sites. So we created the database SitEx that keep the information about this mapping and included the BLAST search and 3D similar structure search using PDB3DScan for the polypeptide encoded by one exon, participating in organizing the functional site. This will help: # to study the positions of the functional sites in exon structure; # to make the complex analysis of the protein function; # to exposure the exons that took part in exon shuffling and came from bacterial genomes; # to study the peculiarities of coding the polypeptide structures. Currently, SitEx contains information about 9994 functional sites presented in 2021 proteins described in proteomes of 17 organisms.

Proper citation: SitEx (RRID:SCR_006122) Copy   

•   Source: SciCrunch Registry

http://idp1.force.cs.is.nagoya-u.ac.jp/pscdb/

Database for protein structural change upon ligand binding that are classified into 7 classes in terms of the ligand binding sites and the location where the dominant motion occurs. # Coupled Domain motions are the domain motions induced upon ligand binding. # Independent Domain motions are the observable domain motions regardless of ligand binding. # Coupled Local motions are the local motions induced upon ligand binding. # Independent Local motions are the observable local motions regardless of ligand binding. # Burying ligand motions are imaginable motions required to hold ligand protein-inside. # No significant motions mean just nothing happen. # Other motions are motions unclassified into domain and local motions. Proteins are flexible molecules that undergo structural changes to function. The Protein Data Bank contains multiple entries for identical proteins determined under different conditions, e.g. with and without a ligand molecule, which provides important information for understanding the structural changes related to protein functions. We gathered 839 protein structural pairs of ligand-free and ligand-bound states from monomeric or homo-dimeric proteins, and constructed the Protein Structural Change DataBase (PSCDB). In the database, we focused on whether the motions were coupled with ligand binding. As a result, the protein structural changes were classified into seven classes, i.e. coupled domain motion (59 structural changes), independent domain motion (70), coupled local motion (125), independent local motion (135), burying ligand motion (104), no significant motion (311) and other type motion (35). PSCDB provides lists of each class. On each entry page, users can view detailed information about the motion, accompanied by a morphing animation of the structural changes.

Proper citation: PSCDB - Protein Structural Change DataBase (RRID:SCR_006116) Copy   

•   Source: SciCrunch Registry

http://newt-omics.mpi-bn.mpg.de/index.php

Newt-omics is a database, which enables researchers to locate, retrieve and store data sets dedicated to the molecular characterization of newts. Newt-omics is a transcript-centered database, based on an Expressed Sequence Tag (EST) data set from the newt, covering ~50,000 Sanger sequenced transcripts and a set of high-density microarray data, generated from regenerating hearts. Newt-omics also contains a large set of peptides identified by mass spectrometry, which was used to validate 13,810 ESTs as true protein coding. Newt-omics is open to implement additional high-throughput data sets without changing the database structure. Via a user-friendly interface Newt-omics allows access to a huge set of molecular data without the need for prior bioinformatical expertise. The newt Notopthalmus viridescens is the master of regeneration. This organism is known for more than 200 years for its exceptional regenerative capabilities. Newts can completely replace lost appendages like limb and tail, lens and retina and parts of the central nervous system. Moreover, after cardiac injury newts can rebuild the functional myocardium with no scar formation. To date only very limited information from public databases is available. Newt-Omics aims to provide a comprehensive platform of expressed genes during tissue regeneration, including extensive annotations, expression data and experimentally verified peptide sequences with yet no homology to other publicly available gene sequences. The goal is to obtain a detailed understanding of the molecular processes underlying tissue regeneration in the newt, that may lead to the development of approaches, efficiently stimulating regenerative pathways in mammalians. * Number of contigs: 26594 * Number of est in contigs: 48537 * Number of transcripts with verified peptide: 5291 * Number of peptides: 15169

Proper citation: Newtomics (RRID:SCR_006073) Copy   

•   Source: SciCrunch Registry