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Sequence Analysis, Protein

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A Machine Learning Approach to Explain Drug Selectivity to Soluble and Membrane Protein Targets.

Molecular informatics
Improved understanding of the forces that determine drug specificity to their targets is important for drug design and discovery, as well as for gaining knowledge about molecular recognition. Here, we present a machine learning approach that includes...

GlycoMine: a machine learning-based approach for predicting N-, C- and O-linked glycosylation in the human proteome.

Bioinformatics (Oxford, England)
MOTIVATION: Glycosylation is a ubiquitous type of protein post-translational modification (PTM) in eukaryotic cells, which plays vital roles in various biological processes (BPs) such as cellular communication, ligand recognition and subcellular reco...

Identification of human drug targets using machine-learning algorithms.

Computers in biology and medicine
Identification of potential drug targets is a crucial task in the drug-discovery pipeline. Successful identification of candidate drug targets in entire genomes is very useful, and computational prediction methods can speed up this process. In the cu...

Prediction of β-lactamase and its class by Chou's pseudo-amino acid composition and support vector machine.

Journal of theoretical biology
β-Lactam class of antibiotics is used as major therapeutic agent against a number of pathogenic microbes. The widespread and indiscriminate use of antibiotics to treat bacterial infection has prompted evolution of several evading mechanisms from the ...

Discrimination of acidic and alkaline enzyme using Chou's pseudo amino acid composition in conjunction with probabilistic neural network model.

Journal of theoretical biology
Enzyme catalysis is one of the most essential and striking processes among of all the complex processes that have evolved in living organisms. Enzymes are biological catalysts, which play a significant role in industrial applications as well as in me...

PFP/ESG: automated protein function prediction servers enhanced with Gene Ontology visualization tool.

Bioinformatics (Oxford, England)
UNLABELLED: Protein function prediction (PFP) is an automated function prediction method that predicts Gene Ontology (GO) annotations for a protein sequence using distantly related sequences and contextual associations of GO terms. Extended similarit...

PseDNA-Pro: DNA-Binding Protein Identification by Combining Chou's PseAAC and Physicochemical Distance Transformation.

Molecular informatics
Identification of DNA-binding proteins is an important problem in biomedical research as DNA-binding proteins are crucial for various cellular processes. Currently, the machine learning methods achieve the-state-of-the-art performance with different ...

MEGA-GO: functions prediction of diverse protein sequence length using Multi-scalE Graph Adaptive neural network.

Bioinformatics (Oxford, England)
MOTIVATION: The increasing accessibility of large-scale protein sequences through advanced sequencing technologies has necessitated the development of efficient and accurate methods for predicting protein function. Computational prediction models hav...

[AcidBasePred: a protein acid-base tolerance prediction platform based on deep learning].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology
The structures and activities of enzymes are influenced by pH of the environment. Understanding and distinguishing the adaptation mechanisms of enzymes to extreme pH values is of great significance for elucidating the molecular mechanisms and promoti...

Deep learning for the PSIPRED Protein Analysis Workbench.

Nucleic acids research
The PSIRED Workbench is a long established and popular bioinformatics web service offering a wide range of machine learning based analyses for characterizing protein structure and function. In this paper we provide an update of the recent additions a...