AIMC Topic: Protein Domains

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iSEE: Interface structure, evolution, and energy-based machine learning predictor of binding affinity changes upon mutations.

Proteins Dec 3, 2018
Quantitative evaluation of binding affinity changes upon mutations is crucial for protein engineering and drug design. Machine learning-based methods are gaining increasing momentum in this field. Due to the limited number of experimental data, using...
Computational Biology Evolution, Molecular Proteins Machine Learning Protein Binding Tumor Suppressor Protein p53 Thermodynamics Models, Molecular Binding, Competitive Mutation Proto-Oncogene Proteins c-mdm2 Protein Domains
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Computational discovery of direct associations between GO terms and protein domains.

BMC bioinformatics Nov 20, 2018
BACKGROUND: Families of related proteins and their different functions may be described systematically using common classifications and ontologies such as Pfam and GO (Gene Ontology), for example. However, many proteins consist of multiple domains, a...
Gene Ontology Proteins Databases, Protein Algorithms Protein Domains Computational Biology Area Under Curve Amino Acid Sequence Molecular Sequence Annotation
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SeqSVM: A Sequence-Based Support Vector Machine Method for Identifying Antioxidant Proteins.

International journal of molecular sciences Jun 15, 2018
Antioxidant proteins can be beneficial in disease prevention. More attention has been paid to the functionality of antioxidant proteins. Therefore, identifying antioxidant proteins is important for the study. In our work, we propose a computational m...
Humans Software Animals Sequence Analysis, Protein Oxidative Stress Support Vector Machine Protein Domains
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DPP-PseAAC: A DNA-binding protein prediction model using Chou's general PseAAC.

Journal of theoretical biology May 16, 2018
A DNA-binding protein (DNA-BP) is a protein that can bind and interact with a DNA. Identification of DNA-BPs using experimental methods is expensive as well as time consuming. As such, fast and accurate computational methods are sought for predicting...
DNA Models, Molecular Protein Domains Computational Biology Support Vector Machine Databases, Protein Nucleic Acid Conformation Amino Acids DNA-Binding Proteins Amino Acid Sequence Algorithms Reproducibility of Results
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Genes sharing the protein family domain decrease the performance of classification with RNA-seq genomic signatures.

Biology direct Feb 21, 2018
BACKGROUND: The experience with running various types of classification on the CAMDA neuroblastoma dataset have led us to the conclusion that the results are not always obvious and may differ depending on type of analysis and selection of genes used ...
Humans Machine Learning Sequence Analysis, RNA Protein Domains
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MoRFPred-plus: Computational Identification of MoRFs in Protein Sequences using Physicochemical Properties and HMM profiles.

Journal of theoretical biology Oct 16, 2017
MOTIVATION: Intrinsically Disordered Proteins (IDPs) lack stable tertiary structure and they actively participate in performing various biological functions. These IDPs expose short binding regions called Molecular Recognition Features (MoRFs) that p...
Amino Acid Sequence Intrinsically Disordered Proteins Binding Sites Protein Binding Models, Theoretical Support Vector Machine Computational Biology Algorithms Protein Domains
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A new model of flavonoids affinity towards P-glycoprotein: genetic algorithm-support vector machine with features selected by a modified particle swarm optimization algorithm.

Archives of pharmacal research Dec 27, 2016
Flavonoids exhibit a high affinity for the purified cytosolic NBD (C-terminal nucleotide-binding domain) of P-glycoprotein (P-gp). To explore the affinity of flavonoids for P-gp, quantitative structure-activity relationship (QSAR) models were develop...
Datasets as Topic Quantitative Structure-Activity Relationship Models, Chemical Protein Domains ATP Binding Cassette Transporter, Subfamily B, Member 1 Protein Binding Support Vector Machine Flavonoids
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Identification of DEP domain-containing proteins by a machine learning method and experimental analysis of their expression in human HCC tissues.

Scientific reports Dec 21, 2016
The Dishevelled/EGL-10/Pleckstrin (DEP) domain-containing (DEPDC) proteins have seven members. However, whether this superfamily can be distinguished from other proteins based only on the amino acid sequences, remains unknown. Here, we describe a com...
Machine Learning Algorithms Phylogeny Gene Expression Profiling Real-Time Polymerase Chain Reaction Liver Neoplasms Protein Domains Humans Amino Acid Motifs GTPase-Activating Proteins Gene Expression Regulation, Neoplastic Dishevelled Proteins Carcinoma, Hepatocellular Signal Transduction Computational Biology Cluster Analysis RNA, Messenger
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gDNA-Prot: Predict DNA-binding proteins by employing support vector machine and a novel numerical characterization of protein sequence.

Journal of theoretical biology Jul 1, 2016
DNA-binding proteins are the functional proteins in cells, which play an important role in various essential biological activities. An effective and fast computational method gDNA-Prot is proposed to predict DNA-binding proteins in this paper, which ...
DNA Numerical Analysis, Computer-Assisted Models, Molecular Support Vector Machine Protein Domains DNA-Binding Proteins ROC Curve Databases, Protein Amino Acid Sequence Computational Biology Principal Component Analysis Genome
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Effectively Identifying Compound-Protein Interactions by Learning from Positive and Unlabeled Examples.

IEEE/ACM transactions on computational biology and bioinformatics May 18, 2016
Prediction of compound-protein interactions (CPIs) is to find new compound-protein pairs where a protein is targeted by at least a compound, which is a crucial step in new drug design. Currently, a number of machine learning based methods have been d...
Support Vector Machine Protein Domains Humans Caenorhabditis elegans Proteins Proteins Pharmaceutical Preparations Databases, Protein Drug Discovery Protein Interaction Mapping Computational Biology
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