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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
http://huanglab.phys.hust.edu.cn/hpepdock/
Web server for blind peptide protein docking based on hierarchical algorithm. Blind peptide-protein docking by fast modeling of peptide conformations and global sampling of binding orientations.
Proper citation: HPEPDOCK Server (RRID:SCR_018561) Copy
https://sciex.com/products/software/proteinpilot-software
Software tool for protein identification and relative protein expression analysis. Used in protein research to identify proteins and search large numbers of post translational modifications. Compatible with all proteomics MS/MS systems.
Proper citation: ProteinPilot Software (RRID:SCR_018681) Copy
Software toolkit for concretely describing non-canonical polymers and complexes to facilitate global biochemical networks. Web tool for describing molecular structure of macromolecular complexes, including non canonical monomeric forms, circular topologies, and crosslinks. Describes semantic meaning of whole cell computational models.
Proper citation: BcForms (RRID:SCR_018654) Copy
http://galaxy.seoklab.org/cgi-bin/submit.cgi?type=REFINE
Web server for protein structure prediction, refinement, and related methods. First rebuilds side chains and performs side-chain repacking and subsequent overall structure relaxation by molecular dynamics simulation.
Proper citation: GalaxyRefine (RRID:SCR_018531) Copy
http://crdd.osdd.net/raghava/toxinpred/
Software package for peptides designing and prediction. In silico approach for predicting toxicity of peptides and proteins. Used for predicting peptide toxicity or non toxicity, minimum mutations in peptides for increasing or decreasing their toxicity, toxic regions in proteins.
Proper citation: ToxinPred (RRID:SCR_018542) Copy
https://www.ncbi.nlm.nih.gov/Structure/bwrpsb/bwrpsb.cgi
Web tool for detection of structural and functional domains in protein sequences. Allows computation and download of conserved domain annotation for large sets of protein queries. Allows to view results graphically. Shows domain footprints, alignment details, and conserved features on any individual query sequence.
Proper citation: Batch Web CD-Search Tool (RRID:SCR_018756) Copy
https://www.iitm.ac.in/bioinfo/PPA_Pred/index.html
Web server for protein protein affinity prediction. Used for predicting binding affinity of protein protein complexes.
Proper citation: PPA-Pred2 (RRID:SCR_018957) Copy
Web based database of proteins, RNA, lipids and metabolites that are identified in extracellular vesicles. Compendium for extracellular vesicles with continuous community annotation and with manually curated data from published literature.
Proper citation: Vesiclepedia (RRID:SCR_019011) Copy
http://www.softberry.com/berry.phtml?topic=fgenes_plus&group=programs&subgroup=gfs
Web tool as HMM plus similar protein based gene prediction. Used for multiple gene prediction in genomic DNA with using information from similar protein. Used if you know protein sequence similar with protein which is encoded by gene in your sequence.
Proper citation: FGENESH Plus (RRID:SCR_018937) Copy
http://msquant.sourceforge.net/
Software tool for quantitative proteomics,mass spectrometry and processes spectra and LC runs to find quantitative information about proteins and peptides. Though automated it also allows manual inspection and change.Entry in MSQuant is Mascot search engine.
Proper citation: MSQuant (RRID:SCR_019206) Copy
The Physiome Project is a worldwide public domain effort to provide a computational framework for understanding human and other eukaryotic physiology. It aims to develop integrative models at all levels of biological organization, from genes to the whole organism via gene regulatory networks, protein pathways, integrative cell function, and tissue and whole organ structure/function relations. Additionally, an important goal of the project is to develop applications for teaching physiology. Current projects include the development of: - ontologies to organize biological knowledge and access to databases - markup languages to encode models of biological structure and function in a standard format for sharing between different application programs and for re-use as components of more comprehensive models - databases of structure at the cell, tissue and organ levels - software to render computational models of cell function such as ion channel electrophysiology, cell signaling and metabolic pathways, transport, motility, the cell cycle, etc. in 2 & 3D graphical form - software for displaying and interacting with the organ models which will allow the user to move across all spatial scales Sponsors: This project is supported by the International Union of Physiological Sciences (IUPS), the IEEE Engineering. in Medicine and Biology (EMBS), and the International Federation for Medical and Biological Engineering (IFMBE)
Proper citation: International Union of Physiological Sciences: Physiome Project (RRID:SCR_001760) Copy
http://dynamicbrain.neuroinf.jp/
THIS RESOURCE IS NO LONGER IN SERVICE, documented on January 19. 2022. Platform to promote studies on dynamic principles of brain functions through unifying experimental and computational approaches in cellular, local circuit, global network and behavioral levels. Provides services such as data sets, popular research findings and articles and current developments in field. This site has been archived since FY2019 and is no longer updated.
Proper citation: Dynamic Brain Platform (RRID:SCR_001754) Copy
A manually curated database of both known and predicted metabolic pathways for the laboratory mouse. It has been integrated with genetic and genomic data for the laboratory mouse available from the Mouse Genome Informatics database and with pathway data from other organisms, including human. The database records for 1,060 genes in Mouse Genome Informatics (MGI) are linked directly to 294 pathways with 1,790 compounds and 1,122 enzymatic reactions in MouseCyc. (Aug. 2013) BLAST and other tools are available. The initial focus for the development of MouseCyc is on metabolism and includes such cell level processes as biosynthesis, degradation, energy production, and detoxification. MouseCyc differs from existing pathway databases and software tools because of the extent to which the pathway information in MouseCyc is integrated with the wealth of biological knowledge for the laboratory mouse that is available from the Mouse Genome Informatics (MGI) database.
Proper citation: MouseCyc (RRID:SCR_001791) Copy
http://www.ncbi.nlm.nih.gov/projects/homology/maps/
This page provides quick access to the Comparative mapping functions available in the Map Viewer. Currently, comparative maps are calculated using HomoloGene orthology predictions. Once the gene pairs have been established, blocks of conserved syteny can be established using the positions of each gene object in their respective builds. Sponsors: This resource is supported by NCBI.
Proper citation: Homology Maps Page (RRID:SCR_001666) Copy
Data analysis service that searches PubMed literature database (abstracts) about specific relationships between proteins, genes, or keywords using a NLP-based text-mining approach. The results are returned as a graph. The synonym database used in Chilibot is available, without fee, for academic use only. Several different search methods are supported including: * searching for relationship between two genes, proteins or keywords * searching for relationships between many genes, proteins, or keywords * searching for relationships between two lists of genes, proteins, or keywords Advanced options include: * Automated hypothesis generation (graph) * Restricting context using keywords * Providing your own synonyms * Modifying synonyms provided by Chilibot * Color coding nodes with gene expression values * Special search: modulation
Proper citation: Chilibot: Gene and Protein relationships from MEDLINE (RRID:SCR_001705) Copy
Database of genetic and molecular biological information about Candida albicans. Contains information about genes and proteins, descriptions and classifications of their biological roles, molecular functions, and subcellular localizations, gene, protein, and chromosome sequence information, tools for analysis and comparison of sequences and links to literature information. Each CGD gene or open reading frame has an individual Locus Page. Genetic loci that are not tied to DNA sequence also have Locus Pages. Provides Gene Ontology, GO, to all its users. Three ontologies that comprise GO (Molecular Function, Cellular Component, and Biological Process) are used by multiple databases to annotate gene products, so that this common vocabulary can be used to compare gene products across species. Development of ontologies is ongoing in order to incorporate new information. Data submissions are welcome.
Proper citation: Candida Genome Database (RRID:SCR_002036) Copy
http://biodev.extra.cea.fr/interoporc/
Automatic prediction tool to infer protein-protein interaction networks, it is applicable for lots of species using orthology and known interactions. The interoPORC method is based on the interolog concept and combines source interaction datasets from public databases as well as clusters of orthologous proteins (PORC) available on Integr8. Users can use this page to ask InteroPorc for all species present in Integr8. Some results are already computed and users can run InteroPorc to investigate any other species. Currently, the following databases are processed and merged (with datetime of the last available public release for each database used): IntAct, MINT, DIP, and Integr8.
Proper citation: InteroPorc (RRID:SCR_002067) Copy
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025. Bioinformatics resource system including web server and web service for functional annotation and enrichment analyses of gene lists. Consists of comprehensive knowledgebase and set of functional analysis tools. Includes gene centered database integrating heterogeneous gene annotation resources to facilitate high throughput gene functional analysis.
Proper citation: DAVID (RRID:SCR_001881) Copy
http://learn.genetics.utah.edu/
Educational resources that provide accurate and unbiased information about topics in genetics, bioscience and health for global and local audiences. They are jargon-free, target multiple learning styles, and often convey concepts through animation and interactivity. The Genetic Science Learning Center is a science and health education program located in the midst of the bioscience research being carried out at the University of Utah. Our mission is making science easy for everyone to understand. * Two websites, available free of charge to Internet users worldwide: ** Learn.Genetics delivers educational materials on genetics, bioscience and health topics. They are designed to be used by students, teachers and members of the public. The materials meet selected US education standards for science and health. ** Teach.Genetics provides resources for K-12 teachers, higher education faculty, and public educators. These include PDF-based Print-and-Go™ activities, unit plans and other supporting resources. The materials are designed to support and extend the materials on Learn.Genetics. *Professional development programs that update K-16 teachers' expertise in bioscience and health topics as well as prepare them to implement the materials on our websites. * Community programs that engage with diverse communities in discussions about genetics and health, and in developing culturally and linguistically-appropriate educational materials. Some topics in genetics and bioscience research are controversial. The Center does not take sides in political or ethical controversies. Rather, our goal is to provide comprehensive information that promotes a lively discussion of these topics, so that individuals can arrive at their own informed decisions.
Proper citation: University of Utah Genetic Science Learning Center - Learn Genetics (RRID:SCR_001910) Copy
http://www.megabionet.org/atpid/webfile/
Centralized platform to depict and integrate the information pertaining to protein-protein interaction networks, domain architecture, ortholog information and GO annotation in the Arabidopsis thaliana proteome. The Protein-protein interaction pairs are predicted by integrating several methods with the Naive Baysian Classifier. All other related information curated is manually extracted from published literature and other resources from some expert biologists. You are welcomed to upload your PPI or subcellular localization information or report data errors. Arabidopsis proteins is annotated with information (e.g. functional annotation, subcellular localization, tissue-specific expression, phosphorylation information, SNP phenotype and mutant phenotype, etc.) and interaction qualifications (e.g. transcriptional regulation, complex assembly, functional collaboration, etc.) via further literature text mining and integration of other resources. Meanwhile, the related information is vividly displayed to users through a comprehensive and newly developed display and analytical tools. The system allows the construction of tissue-specific interaction networks with display of canonical pathways.
Proper citation: Arabidopsis thaliana Protein Interactome Database (RRID:SCR_001896) Copy
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