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https://www.ddg-pharmfac.net/AllerTOP/
Web server for in silico prediction of allergens. Alignment free server for in silico prediction of allergens based on main physicochemical properties of proteins. Used to predict the route of allergen exposure: food, inhalant or toxin.
Proper citation: AllerTop (RRID:SCR_018496) Copy
https://prosa.services.came.sbg.ac.at/prosa.php
Web service is extension of classic ProSA program used for refinement and validation of experimental protein structures and in structure prediction and modeling.
Proper citation: ProSA-web (RRID:SCR_018540) Copy
https://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi
Web tool for conserved domains searching within protein or coding nucleotide sequence.
Proper citation: Conserved Domains Search (RRID:SCR_018729) Copy
Web platform for downstream analysis and visualization of proteomics data. Server that facilitates integrated annotation, analysis and visualization of quantitative proteomics data, with emphasis on PTM networks and integration with LINCS library of chemical and genetic perturbation signatures in order to provide further mechanistic and functional insights. Primary input for server consists of set of peptides or proteins, optionally with PTM sites, and their corresponding abundance values.
Proper citation: piNET (RRID:SCR_018693) Copy
Web tool as protein structure prediction service. Provides automated structure prediction and analysis tools that can be used to infer protein structural information from genomic data. Produces model for entire protein sequence in presence or absence of sequence homology to protein of known structure.
Proper citation: Robetta (RRID:SCR_018805) Copy
http://protein.ict.ac.cn/FALCON/
Web tool as high throughput protein structure prediction service. High throughput server for protein structure prediction.
Proper citation: FALCON (RRID:SCR_018804) Copy
Software toolkit for unambiguously describing molecular structure of DNA, RNA, and proteins, including non-canonical monomeric forms, crosslinks, nicks, and circular topologies. Aims to help epigenomics, transcriptomics, proteomics, systems biology, and synthetic biology researchers share and integrate information about DNA modification, post-transcriptional modification, post-translational modification, expanded genetic codes, and synthetic parts.
Proper citation: BpForms (RRID:SCR_018653) Copy
http://tools.dice-database.org/GOnet/)
Web tool for interactive Gene Ontology analysis of any biological data sources resulting in gene or protein lists.
Proper citation: GOnet (RRID:SCR_018977) Copy
https://www.ebi.ac.uk/thornton-srv/software/PROCHECK/
Software tool to check stereochemical quality of protein structures. Its outputs comprise number of plots in PostScript format and comprehensive residue by residue listing. Includes PROCHECK-NMR for checking quality of structures solved by NMR.
Proper citation: PROCHECK (RRID:SCR_019043) Copy
Web application for visualisation of information derived from residue contact predictions in combination with other sources of information, such as secondary structure predictions, transmembrane helical topology, sequence conservation.Provides interactive interface for researchers in field of protein bioinformatics that are interested in analysing data on given protein.
Proper citation: ConPlot (RRID:SCR_019216) Copy
http://noble.gs.washington.edu/proj/sdp-svm/
A statistical framework for genomic data fusion is a computational framework for integrating and drawing inferences from a collection of genome-wide measurements. Each dataset is represented via a kernel function, which defines generalized similarity relationships between pairs of entities, such as genes or proteins. The kernel representation is both flexible and efficient, and can be applied to many different types of data. Furthermore, kernel functions derived from different types of data can be combined in a straightforward fashion. Recent advances in the theory of kernel methods have provided efficient algorithms to perform such combinations in a way that minimizes a statistical loss function. These methods exploit semidefinite programming techniques to reduce the problem of finding optimizing kernel combinations to a convex optimization problem. Computational experiments performed using yeast genome-wide datasets, including amino acid sequences, hydropathy profiles, gene expression data and known protein-protein interactions, demonstrate the utility of this approach. A statistical learning algorithm trained from all of these data to recognize particular classes of proteins--membrane proteins and ribosomal proteins--performs significantly better than the same algorithm trained on any single type of data. Matlab code to center a kernel matrix and Matlab code for normalization are available.
Proper citation: A statistical framework for genomic data fusion (RRID:SCR_007219) Copy
http://wiki.c2b2.columbia.edu/califanolab/index.php/BCellInteractome.htm
A network of protein-protein, protein-DNA and modulatory interactions in human B cells. The network contains known interactions (reported in public databases) and predicted interactions by a Bayesian evidence integration framework which integrates a variety of generic and context specific experimental clues about protein-protein and protein-DNA interactions with inferences from different reverse engineering algorithms, such as GeneWays and ARACNE. Modulatory interactions are predicted by the MINDY, an algorithm for the prediction of modulators of transcriptional interactions (please refer to the publication section for more information). The BCI can be downloaded as one tab delimited file containing the complete network (BCI.txt) with each type of interaction explicitly defined.
Proper citation: B Cell Interactome (RRID:SCR_008655) Copy
http://lincsportal.ccs.miami.edu/dcic-portal/
Portal which provides a unified interface for searching LINCS dataset packages and reagents. Users can use the portal to access datasets, small molecules, cells, genes, proteins and peptides, and antibodies.
Proper citation: LINCS Data Portal (RRID:SCR_014939) Copy
https://www.synapse.org/#!Synapse:syn4921369/wiki/235539
Portal of PsychENCODE Consortium to study role of rare genetic variants involved in several psychiatric disorders. Database of regulatory elements, epigenetic modifications, RNA and protein in brain.
Proper citation: PsychENCODE Knowledge Portal (RRID:SCR_017500) Copy
Software that detects kinase-specific phosphorylation sites. GPS provides a platform able to perform its prediction based on a group-based phosphorylation scoring algorithm. It allows users to query multiple protein sequences through a batch prediction mode.
Proper citation: GPS (RRID:SCR_016374) Copy
THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. It offers short, structured reviews of proteins and protein families, especially leukocyte surface membrane molecules. Index of information available from PROW includes CD molecule, Alternate names, Current Guides, Past Guides, Entrez Gene and Assigning workshop. Current guides: expanded format including Summary Sentence and Abstract Past guides: older guides with excellent information, some data may be dated
Proper citation: PROW (RRID:SCR_002434) Copy
http://biology.hunter.cuny.edu/index.php?option=com_content&view=article&id=138&Itemid=117
Facility which provides instruments and instrument resources for analyzing DNA, RNA, protein, and radio-labeled substances.
Proper citation: Hunter Genomic Facility (RRID:SCR_001983) Copy
The EBI genomes pages give access to a large number of complete genomes including bacteria, archaea, viruses, phages, plasmids, viroids and eukaryotes. Methods using whole genome shotgun data are used to gain a large amount of genome coverage for an organism. WGS data for a growing number of organisms are being submitted to DDBJ/EMBL/GenBank. Genome entries have been listed in their appropriate category which may be browsed using the website navigation tool bar on the left. While organelles are all listed in a separate category, any from Eukaryota with chromosome entries are also listed in the Eukaryota page. Within each page, entries are grouped and sorted at the species level with links to the taxonomy page for that species separating each group. Within each species, entries whose source organism has been categorized further are grouped and numbered accordingly. Links are made to: * taxonomy * complete EMBL flatfile * CON files * lists of CON segments * Project * Proteomes pages * FASTA file of Proteins * list of Proteins
Proper citation: EBI Genomes (RRID:SCR_002426) Copy
http://www.linked-neuron-data.org/
Neuroscience data and knowledge from multiple scales and multiple data sources that has been extracted, linked, and organized to support comprehensive understanding of the brain. The core is the CAS Brain Knowledge base, a very large scale brain knowledge base based on automatic knowledge extraction and integration from various data and knowledge sources. The LND platform provides services for neuron data and knowledge extraction, representation, integration, visualization, semantic search and reasoning over the linked neuron data. Currently, LND extracts and integrates semantic data and knowledge from the following resources: PubMed, INCF-CUMBO, Allen Reference Atlas, NIF, NeuroLex, MeSH, DBPedia/Wikipedia, etc.
Proper citation: Linked Neuron Data (RRID:SCR_003658) Copy
A database ofhuman disease-related mutated proteins identified by mass-spectrometry (MS). For achieving this goal, we collected human mutated sequences known to be related to diseases till now. After surveying mutated sequence sources: PMD, OMIM, SwissProt polymorphism, HGMD, etc, we found that currently HGMD contains the largest human gene mutation information. However, because, for academic users, HGMD does not provide with whole data download service, we decided to systematically extract and curate mutation information from PMD, OMIM, SwissProt, MSIPI database to form SysPIMP and provide it free for academic users.
Proper citation: Systematic Platform for Identifying Mutated Proteins (SysPIMP) (RRID:SCR_007954) Copy
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