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Identification of Glucose-Binding Pockets in Human Serum Albumin Using Support Vector Machine and Molecular Dynamics Simulations.

IEEE/ACM transactions on computational biology and bioinformatics Jan 1, 2016
Human Serum Albumin (HSA) has been suggested to be an alternate biomarker to the existing Hemoglobin-A1c (HbA1c) marker for glycemic monitoring. Development and usage of HSA as an alternate biomarker requires the identification of glycation sites, or...
Computational Biology Support Vector Machine Glucose Molecular Dynamics Simulation Serum Albumin Binding Sites Humans Protein Binding
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Use of machine learning approaches for novel drug discovery.

Expert opinion on drug discovery Jan 1, 2016
INTRODUCTION: The use of computational tools in the early stages of drug development has increased in recent decades. Machine learning (ML) approaches have been of special interest, since they can be applied in several steps of the drug discovery met...
Machine Learning Molecular Docking Simulation Drug Design Humans Neural Networks, Computer Models, Biological Ligands Binding Sites Drug Discovery Support Vector Machine Decision Trees
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A systematic approach to prioritize drug targets using machine learning, a molecular descriptor-based classification model, and high-throughput screening of plant derived molecules: a case study in oral cancer.

Molecular bioSystems Dec 1, 2015
Systems-biology inspired identification of drug targets and machine learning-based screening of small molecules which modulate their activity have the potential to revolutionize modern drug discovery by complementing conventional methods. To utilize ...
Gene Regulatory Networks Protein Binding Computational Biology Cell Line, Tumor ROC Curve Models, Molecular Mouth Neoplasms High-Throughput Screening Assays Gene Expression Regulation, Neoplastic Antineoplastic Agents, Phytogenic Receptors, CXCR4 Humans Machine Learning Drug Discovery Protein Interaction Mapping Molecular Conformation Binding Sites
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Distinct Transcriptional and Anti-Mycobacterial Profiles of Peripheral Blood Monocytes Dependent on the Ratio of Monocytes: Lymphocytes.

EBioMedicine Nov 1, 2015
The ratio of monocytes and lymphocytes (ML ratio) in peripheral blood is associated with tuberculosis and malaria disease risk and cancer and cardiovascular disease outcomes. We studied anti-mycobacterial function and the transcriptome of monocytes i...
Lymphocytes Gene Expression Profiling Young Adult Protein Binding Disease Susceptibility Humans Adult Mycobacterium Transcriptome Binding Sites Male Monocytes Leukocyte Count Signal Transduction Transcription Factors Interferons Tuberculosis Disease Resistance Female
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Predicting Protein-Protein Interaction Sites with a Novel Membership Based Fuzzy SVM Classifier.

IEEE/ACM transactions on computational biology and bioinformatics Jan 1, 2015
Predicting residues that participate in protein-protein interactions (PPI) helps to identify, which amino acids are located at the interface. In this paper, we show that the performance of the classical support vector machine (SVM) algorithm can furt...
Sequence Alignment Sequence Analysis, Protein Binding Sites Protein Interaction Mapping Molecular Sequence Data Amino Acid Sequence Pattern Recognition, Automated Algorithms Computer Simulation Protein Binding Fuzzy Logic Models, Statistical Models, Chemical Humans
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Prediction of protein-protein interaction sites from weakly homologous template structures using meta-threading and machine learning.

Journal of molecular recognition : JMR Jan 1, 2015
The identification of protein-protein interactions is vital for understanding protein function, elucidating interaction mechanisms, and for practical applications in drug discovery. With the exponentially growing protein sequence data, fully automate...
Machine Learning Software Hydrogen Bonding Binding Sites Algorithms Evolution, Molecular Protein Binding Proteins Models, Molecular
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Constructing query-driven dynamic machine learning model with application to protein-ligand binding sites prediction.

IEEE transactions on nanobioscience Jan 1, 2015
We are facing an era with annotated biological data rapidly and continuously generated. How to effectively incorporate new annotated data into the learning step is crucial for enhancing the performance of a bioinformatics prediction model. Although m...
Machine Learning Protein Binding Proteins Databases, Protein Ligands Models, Biological Binding Sites Nucleotides
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