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http://www.bondxray.org/software/aline.html

Software interactive perl/tk application which can read common sequence alignment formats which the user can then alter, embellish, markup etc to produce the kind of sequence figure commonly found in biochemical articles. Extensible WYSIWYG protein sequence alignment editor for publication quality figures.

Proper citation: Aline (RRID:SCR_016886) Copy   

•   Source: SciCrunch Registry

http://emboss.sourceforge.net/apps/cvs/embassy/index.html#DOMAINATRIX

Software for protein domain search. It is a part of Embassy software package.

Proper citation: DOMAINATRIX (RRID:SCR_016084) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.albany.edu/~dmaps

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 6, 2016. DMAPS database contains pre-computed multiple structure alignments for protein chains in the Protein Data Bank (PDB). Automated structure alignments have been generated for classified protein families using CE-MC algorithm. Alignments have been built only for those families with at least three members. Currently, multiple structure alignments are available for 3050 SCOP-, 3087 CATH-, 664 ENZYME- and 1707 CE-based families. Users will be able to retrieve multiple alignments for a given PDB chain classified by one of these criteria.

Proper citation: DMAPS - A Database of Multiple Alignments for Protein Structures (RRID:SCR_007140) Copy   

•   Source: SciCrunch Registry

http://bioinfo.pl/

This service offers a gateway to well-benchmarked protein structure and function prediction methods. Structural models collected from the prediction servers are assessed using the powerful 3D-jury consensus approach. The Structure Prediction Meta Server provides access to various fold recognition, function prediction and local structure prediction methods. The Server takes the amino acid sequence of the query protein, the reference name for the prediction job, and the E-mail address as input. The E-mail address is used only for notification about errors during the execution of the job. The query sequence and the reference name are placed in the process queue. The Meta Server accepts only sequences, which have not been submitted before. In case of duplicate sequences the second user will be notified with a link to the previous submission. Sequences longer than 800 amino acids are not accepted by some services. The internal SQL database offers the possibility to find any previous jobs processed by the Meta Server using regular expressions addressing field like E-mail, Job Name and the host name, from which the job was initiated. Each server has its own process queuing system managed by the Meta Server. All results of fold recognition servers are translated into uniform formats. The information extracted from the raw output of the servers includes the PDB codes of the hits, the alignments and the similarity (reliability) scores specific for every server. Mapping of the hits to the SCOP and FSSP classifications are made either using known PDB representatives or alignment of the template sequence with the databases of proteins in both classifications. The secondary structure assignments for all hits are taken from the mapped FSSP (red for helices and blue for strands). Underscored amino acids indicate the first residue after an insertion in the template sequence. The Meta server provides translation of the alignments in standard formats like FASTA, PDB or CASP. The Meta Server is coupled to consensus servers. They provide jury predictions based on the results collected from other services. Not all fold recognition servers are used by the jury system. The data stored on the meta server is available through http://meta.bioinfo.pl/data/JOBID/. Jobs older than 2 months are not shown. The Meta Server is only a set of programs aimed to process and manage biological data, while the predictive power of the service comes from (mostly) remote prediction providers. Sponsors: This resource is supported by The BioInfoBank Institute.

Proper citation: BioInfoBank Meta Server (RRID:SCR_007181) Copy   

•   Source: SciCrunch Registry

https://omicssimla.sourceforge.io

Software tool for generating multi omics data with disease status. Simulates genomics (SNPs and copy number variations), epigenomics ( whole genome bisulphite sequencing), transcriptomics ( RNA seq), and proteomics (normalized reverse phase protein array) data at the whole genome level. Available as desktop and web application version.

Proper citation: OmicsSIMLA (RRID:SCR_017011) Copy   

•   Source: SciCrunch Registry

http://bioinf.scri.sari.ac.uk/cgi-bin/atnopdb/home

Database of proteins found in the nucleoli of Arabidopsis, identified through proteomic analysis. The Arabidopsis Nucleolar Protein database (AtNoPDB) provides information on the plant proteins in comparison to human and yeast proteins, and images of cellular localizations for over a third of the proteins. A proteomic analysis was carried out of nucleoli purified from Arabidopsis cell cultures and to date 217 proteins have been identified. Many proteins were known nucleolar proteins or proteins involved in ribosome biogenesis. Some proteins, such as spliceosomal and snRNP proteins, and translation factors, were unexpected. In addition, proteins of unknown function which were either plant-specific or conserved between human and plant, and proteins with differential localizations were identified.

Proper citation: Arabidopsis Nucleolar Protein Database (RRID:SCR_001793) 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

http://www.jstacs.de/index.php/GeMoMa

Software tool as homology based gene prediction program that predicts gene models in target species based on gene models in evolutionary related reference species. Utilizes amino acid sequence conservation, intron position conservation, and RNA-seq data to accurately predict protein-coding transcripts. Supports combination of predictions based on several reference species allowing to transfer high quality annotation of different reference species to target species.

Proper citation: GeMoMa (RRID:SCR_017646) Copy   

•   Source: SciCrunch Registry

https://www.schrodinger.com/protein-preparation-wizard

Software tool for correcting common structural problems and creating reliable, all atom protein models.

Proper citation: Protein preparation Wizard (RRID:SCR_016749) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://physiomeproject.org/

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   

•   Source: SciCrunch Registry

http://www.structuralgenomics.org/

The Structural Genomics Project aims at determination of the 3D structure of all proteins. It also aims to reduce the cost and time required to determine three-dimensional protein structures. It supports selection, registration, and tracking of protein families and representative targets. This aim can be achieved in four steps : -Organize known protein sequences into families. -Select family representatives as targets. -Solve the 3D structure of targets by X-ray crystallography or NMR spectroscopy. -Build models for other proteins by homology to solved 3D structures. PSI has established a high-throughput structure determination pipeline focused on eukaryotic proteins. NMR spectroscopy is an integral part of this pipeline, both as a method for structure determinations and as a means for screening proteins for stable structure. Because computational approaches have estimated that many eukaryotic proteins are highly disordered, about 1 year into the project, CESG began to use an algorithm. The project has been organized into two separate phases. The first phase was dedicated to demonstrating the feasibility of high-throughput structure determination, solving unique protein structures, and preparing for a subsequent production phase. The second phase, PSI-2, has focused on implementing the high-throughput structure determination methods developed in PSI-1, as well as homology modeling and addressing bottlenecks like modeling membrane proteins. The first phase of the Protein Structure Initiative (PSI-1) saw the establishment of nine pilot centers focusing on structural genomics studies of a range of organisms, including Arabidopsis thaliana, Caenorhabditis elegans and Mycobacterium tuberculosis. During this five-year period over 1,100 protein structures were determined, over 700 of which were classified as unique due to their < 30% sequence similarity with other known protein structures. The primary goal of PSI-1 was to develop methods to streamline the structure determination process, resulted in an array of technical advances. Several methods developed during PSI-1 enhanced expression of recombinant proteins in systems like Escherichia coli, Pichia pastoris and insect cell lines. New streamlined approaches to cell cloning, expression and protein purification were also introduced, in which robotics and software platforms were integrated into the protein production pipeline to minimize required manpower, increase speed, and lower costs. The goal of the second phase of the Protein Structure Initiative (PSI-2) is to use methods introduced in PSI-1 to determine a large number of proteins and continue development in streamlining the structural genomics pipeline. Currently, the third phase of the PSI is being developed and will be called PSI: Biology. The consortia will propose work on substantial biological problems that can benefit from the determination of many protein structures Sponsors: PSI is funded by the U.S. National Institute of General Medical Sciences (NIGMS),

Proper citation: Protein Structure Initiative (RRID:SCR_002161) Copy   

•   Source: SciCrunch Registry

https://pathoman.mskcc.org/

Web application to automate germline genomic variant curation from clinical sequencing based on ACMG guidelines. Aggregates multiple tracks of genomic, protein and disease specific information from public sources.

Proper citation: PathoMAN (RRID:SCR_026552) Copy   

•   Source: SciCrunch Registry

http://proteininformationresource.org/

Integrated public bioinformatics resource to support genomic, proteomic and systems biology research and scientific studies. Provides databases and protein sequence analysis tools to scientific community, including Protein Sequence Database which grew out from the Atlas of Protein Sequence and Structure. Conducts research in biomedical text mining and ontology, computational systems biology, and bioinformatics cyberinfrastructure. In 2002 PIR, along with its international partners, EBI (European Bioinformatics Institute) and SIB (Swiss Institute of Bioinformatics), were awarded a grant from NIH to create UniProt, a single worldwide database of protein sequence and function, by unifying the PIR-PSD, Swiss-Prot, and TrEMBL databases. Currently, PIR major activities include: i) UniProt (Universal Protein Resource) development, ii) iProClass protein data integration and ID mapping, iii) PRO protein ontology, and iv) iProLINK protein literature mining and ontology development. The FTP site provides free download for iProClass, PIRSF, and PRO.

Proper citation: Protein Information Resource (RRID:SCR_002837) Copy   

•   Source: SciCrunch Registry

http://www.geneatlas.org/gene/main.jsp

This website allows visitors to search for genes of interest based on their spatial expression patterns in the Postnatal Day 7 mouse brain. Geneatlas provides two searching tools: A graphical interface for customized spatial queries; A textual interface for querying annotated structures. Geneatlas is the product of a collaboration between researchers at Baylor College of Medicine, Rice University, and University of Houston.

Proper citation: Gene Atlas (RRID:SCR_008089) Copy   

•   Source: SciCrunch Registry

https://www.livercellatlas.org

Portal to search liver single cell RNA-sequencing datasets. Datasets for expression of genes or proteins (when CITE-seq was performed). To search for gene enter the official gene name. To search for protein please click to see specific names to use for different markers included.

Proper citation: Liver cell atlas (RRID:SCR_023627) Copy   

•   Source: SciCrunch Registry

https://github.com/eduardporta/e-Driver

Software tool to identify cancer driver genes based on linear annotations of biological regions such as protein domains.Uses information on three-dimensional structures of mutated proteins to identify specific structural features. Then algorithm analyzes whether these features are enriched in cancer somatic mutations and are candidate driver genes.

Proper citation: e-Driver (RRID:SCR_002674) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/resources/software/vagrent/

Software tool set for calculating the biological consequences of genomic variations. The suite of perl modules compares genomic variations with reference genome annotations and generates the possible effects each variant may have on the transcripts it overlaps. It evaluates each variation/transcript combination and describes the effects in the mRNA, CDS and protein sequence contexts. It provides details of the sequence and position of the change within the transcript / protein as well as Sequence Ontology terms to classify its consequences.

Proper citation: VAGrENT (RRID:SCR_005180) Copy   

•   Source: SciCrunch Registry

https://services.healthtech.dtu.dk/services/NetNGlyc-1.0/

Server that predicts N-Glycosylation sites in human proteins using artificial neural networks that examine the sequence context of Asn-Xaa-Ser/Thr sequons. NetNGlyc 1.0 is also available as a stand-alone software package, with the same functionality as the service above. Ready-to-ship packages exist for the most common UNIX platforms.

Proper citation: NetNGlyc (RRID:SCR_001570) Copy   

•   Source: SciCrunch Registry