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With BAR 3.0 and a sequence you can annotate when possible: function (Gene Ontology), structure (Protein Data Bank), protein domains (Pfam). Also if your sequence falls into a cluster with a structural/some structural template/s we provide an alignment towards the template/templates based on the Cluster-HMM (HMM profile) that allows you to ...
Proteome Analyst (PA) is a freely available web server and online toolkit for predicting protein subcellular localization, or where a protein resides in a cell. [1] [2] In the field of proteomics, accurately predicting a protein's subcellular localization, or where a specific protein is located inside a cell, is an important step in the large scale study of proteins.
To predict the function, structure, or other properties of a protein for which only its sequence of amino acids is known, the protein sequence is compared to the sequences of other proteins in public databases. If a protein with sufficiently similar sequence is found, the two proteins are likely to be evolutionarily related ("homologous"). In ...
Algorithm and program for comparing primary biological sequence information, including DNA and protein sequences. Cross-platform: Public domain: National Center for Biotechnology Information: CP2K: Perform atomistic simulations of solid state, liquid, molecular and biological systems, written in Fortran 2003. Linux, macOS, Windows: GPL and LGPL
The four search types phmmer, hmmsearch, hmmscan and jackhmmer are supported (see Programs). The search function accepts single sequences as well as sequence alignments or profile HMMs. [10] The search results are accompanied by a report on the taxonomic breakdown, and the domain organisation of the hits. Search results can then be filtered ...
Amyloidogenicity propensity predictor based on a machine learning approach through recursive feature selection and feed-forward neural networks, taking advantage of newly published sequences with experimental, in vitro, evidence of amyloid formation. sequence - Amyloidogenic regions ArchCandy [37] 2015 Download- BiSMM: Secondary structure-related
Casanovo is a machine learning model that uses a transformer neural network architecture to translate the sequence of peaks in a tandem mass spectrum into the sequence of amino acids that comprise the generating peptide, enabling de novo peptide sequencing without prior information. [34] InstaNovo Open source
At that time, Generate announced its focus on using machine learning algorithms and big data to design biological compounds targeting multiple diseases, including SARS-CoV-2, the virus causing COVID-19. Its computational platform integrated vast datasets of protein structures and genetic sequences to develop governing rules for designing new ...