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  2. List of protein subcellular localization prediction tools

    en.wikipedia.org/wiki/List_of_protein_sub...

    This list of protein subcellular localisation prediction tools includes software, databases, and web services that are used for protein subcellular localization prediction. Some tools are included that are commonly used to infer location through predicted structural properties, such as signal peptide or transmembrane helices , and these tools ...

  3. Protein–protein interaction prediction - Wikipedia

    en.wikipedia.org/wiki/Proteinprotein...

    Protein–protein interaction prediction is a field combining bioinformatics and structural biology in an attempt to identify and catalog physical interactions between pairs or groups of proteins. Understanding protein–protein interactions is important for the investigation of intracellular signaling pathways, modelling of protein complex ...

  4. Protein–lipid interaction - Wikipedia

    en.wikipedia.org/wiki/Proteinlipid_interaction

    Protein–lipid interaction is the influence of membrane proteins on the lipid physical state or vice versa. The questions which are relevant to understanding of the structure and function of the membrane are: 1) Do intrinsic membrane proteins bind tightly to lipids (see annular lipid shell ), and what is the nature of the layer of lipids ...

  5. scikit-learn - Wikipedia

    en.wikipedia.org/wiki/Scikit-learn

    scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...

  6. PSIPRED - Wikipedia

    en.wikipedia.org/wiki/PSIPRED

    PSI-blast based secondary structure PREDiction (PSIPRED) is a method used to investigate protein structure. It uses artificial neural network machine learning methods in its algorithm. [ 2 ] [ 3 ] [ 4 ] It is a server-side program, featuring a website serving as a front-end interface, which can predict a protein's secondary structure ( beta ...

  7. Protein aggregation predictors - Wikipedia

    en.wikipedia.org/wiki/Protein_aggregation_predictors

    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

  8. Link prediction - Wikipedia

    en.wikipedia.org/wiki/Link_prediction

    In network theory, link prediction is the problem of predicting the existence of a link between two entities in a network. Examples of link prediction include predicting friendship links among users in a social network, predicting co-authorship links in a citation network, and predicting interactions between genes and proteins in a biological network.

  9. List of disorder prediction software - Wikipedia

    en.wikipedia.org/wiki/List_of_disorder...

    Energy resulting from inter-residue interactions, estimated from local amino acid composition No No MobiDB-lite [7] 2017 Consensus-based prediction of residue disorder Eight separate disorder predictors from various groups No No SPOT-Disorder [8] 2017 Outputs the probability of each residue in a protein sequence of being disordered or ordered.

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