AIMC Topic: Amino Acid Sequence

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Designing Anticancer Peptides by Constructive Machine Learning.

ChemMedChem May 29, 2018
Constructive (generative) machine learning enables the automated generation of novel chemical structures without the need for explicit molecular design rules. This study presents the experimental application of such a deep machine learning model to d...
Antineoplastic Agents Deep Learning MCF-7 Cells Amino Acid Sequence Humans Peptides Drug Design
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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...
Computational Biology Support Vector Machine Databases, Protein Algorithms Reproducibility of Results Nucleic Acid Conformation Amino Acids DNA-Binding Proteins Amino Acid Sequence DNA Models, Molecular Protein Domains
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Identifying 5-methylcytosine sites in RNA sequence using composite encoding feature into Chou's PseKNC.

Journal of theoretical biology May 1, 2018
This study examines accurate and efficient computational method for identification of 5-methylcytosine sites in RNA modification. The occurrence of 5-methylcytosine (mC) plays a vital role in a number of biological processes. For better comprehension...
High-Throughput Nucleotide Sequencing Base Sequence 5-Methylcytosine Amino Acids Amino Acid Sequence RNA Models, Theoretical Support Vector Machine Humans Proteins Algorithms
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HMMER Cut-off Threshold Tool (HMMERCTTER): Supervised classification of superfamily protein sequences with a reliable cut-off threshold.

PloS one Mar 26, 2018
BACKGROUND: Protein superfamilies can be divided into subfamilies of proteins with different functional characteristics. Their sequences can be classified hierarchically, which is part of sequence function assignation. Typically, there are no clear s...
Computational Biology Proteomics Cluster Analysis Proteins Supervised Machine Learning Amino Acid Sequence
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SPIN2: Predicting sequence profiles from protein structures using deep neural networks.

Proteins Mar 25, 2018
Designing protein sequences that can fold into a given structure is a well-known inverse protein-folding problem. One important characteristic to attain for a protein design program is the ability to recover wild-type sequences given their native bac...
Amino Acid Sequence Protein Structure, Secondary Protein Folding Proteins Databases, Protein Models, Molecular Neural Networks, Computer Software
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MUFOLD-SS: New deep inception-inside-inception networks for protein secondary structure prediction.

Proteins Mar 12, 2018
Protein secondary structure prediction can provide important information for protein 3D structure prediction and protein functions. Deep learning offers a new opportunity to significantly improve prediction accuracy. In this article, a new deep neura...
Amino Acids Amino Acid Sequence Binding Sites Protein Binding Proteins Models, Molecular Protein Structure, Secondary Software Algorithms Deep Learning
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MetaGO: Predicting Gene Ontology of Non-homologous Proteins Through Low-Resolution Protein Structure Prediction and Protein-Protein Network Mapping.

Journal of molecular biology Mar 10, 2018
Homology-based transferal remains the major approach to computational protein function annotations, but it becomes increasingly unreliable when the sequence identity between query and template decreases below 30%. We propose a novel pipeline, MetaGO,...
Sequence Analysis, Protein Models, Molecular Internet Amino Acid Sequence Protein Interaction Maps Software Protein Conformation Protein Interaction Mapping Computational Biology Algorithms Sequence Homology, Amino Acid Gene Ontology Proteins Reproducibility of Results
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Structure-function properties of hypolipidemic peptides.

Journal of food biochemistry Mar 8, 2018
This review addresses the structure-function properties of hypolipidemic peptides. The cholesterol-lowering peptide (lactostatin: IIAEK) operates via a new regulatory pathway in the calcium-channel-related mitogen-activated protein kinase (MAPK) sign...
Atherosclerosis Globulins Anti-Obesity Agents Amino Acid Sequence Hypolipidemic Agents Humans Hyperlipidemias Carrier Proteins Membrane Glycoproteins Soybean Proteins Structure-Activity Relationship Oligopeptides Antigens, Plant Apolipoprotein A-I Seed Storage Proteins
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Recurrent Neural Network Model for Constructive Peptide Design.

Journal of chemical information and modeling Jan 22, 2018
We present a generative long short-term memory (LSTM) recurrent neural network (RNN) for combinatorial de novo peptide design. RNN models capture patterns in sequential data and generate new data instances from the learned context. Amino acid sequenc...
Peptides Models, Chemical Amino Acid Sequence Neural Networks, Computer Machine Learning Anti-Infective Agents
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iMem-2LSAAC: A two-level model for discrimination of membrane proteins and their types by extending the notion of SAAC into chou's pseudo amino acid composition.

Journal of theoretical biology Jan 11, 2018
Membrane proteins execute significant roles in cellular processes of living organisms, ranging from cell signaling to cell adhesion. As a major part of a cell, the identification of membrane proteins and their functional types become a challenging jo...
Computational Biology Membrane Proteins Support Vector Machine Databases, Protein Amino Acid Sequence Sequence Analysis, Protein Neural Networks, Computer Algorithms Reproducibility of Results
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