AIMC Topic: Amino Acid Motifs

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Protein structure search to support the development of protein structure prediction methods.

Proteins Feb 2, 2021
Protein structure prediction is a long-standing unsolved problem in molecular biology that has seen renewed interest with the recent success of deep learning with AlphaFold at CASP13. While developing and evaluating protein structure prediction metho...
Humans Research Design Amino Acid Motifs Structural Homology, Protein Protein Conformation, alpha-Helical Deep Learning Protein Conformation, beta-Strand Proteins Benchmarking Sequence Alignment
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Pippin: A random forest-based method for identifying presynaptic and postsynaptic neurotoxins.

Journal of bioinformatics and computational biology May 5, 2020
Presynaptic and postsynaptic neurotoxins are two types of neurotoxins from venomous animals and functionally important molecules in the neurosciences; however, their experimental characterization is difficult, time-consuming, and costly. Therefore, b...
Amino Acid Motifs Neurotoxins Animals Computational Biology Databases, Protein Synapses Machine Learning Algorithms
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Representation learning of genomic sequence motifs with convolutional neural networks.

PLoS computational biology Dec 19, 2019
Although convolutional neural networks (CNNs) have been applied to a variety of computational genomics problems, there remains a large gap in our understanding of how they build representations of regulatory genomic sequences. Here we perform systema...
Transcription Factors Databases, Genetic DNA Genome, Human Binding Sites Computer Simulation Humans Amino Acid Motifs Deep Learning Neural Networks, Computer Genomics Computational Biology
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Prediction of ATP-binding sites in membrane proteins using a two-dimensional convolutional neural network.

Journal of molecular graphics & modelling Jul 15, 2019
Membrane proteins, the most important drug targets, account for around 30% of total proteins encoded by the genome of living organisms. An important role of these proteins is to bind adenosine triphosphate (ATP), facilitating crucial biological proce...
Algorithms Reproducibility of Results ROC Curve Computational Biology Neural Networks, Computer Machine Learning Adenosine Triphosphate Binding Sites Amino Acid Motifs Web Browser Membrane Proteins Models, Theoretical Databases, Protein Amino Acid Sequence Position-Specific Scoring Matrices
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Capturing the differences between humoral immunity in the normal and tumor environments from repertoire-seq of B-cell receptors using supervised machine learning.

BMC bioinformatics May 28, 2019
BACKGROUND: The recent success of immunotherapy in treating tumors has attracted increasing interest in research related to the adaptive immune system in the tumor microenvironment. Recent advances in next-generation sequencing technology enabled the...
Complementarity Determining Regions Receptors, Antigen, B-Cell Immunity, Humoral Databases, Genetic Area Under Curve Supervised Machine Learning Amino Acid Sequence Immunoglobulins High-Throughput Nucleotide Sequencing Amino Acid Motifs Humans Algorithms Tumor Microenvironment ROC Curve
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Large-scale network analysis reveals the sequence space architecture of antibody repertoires.

Nature communications Mar 21, 2019
The architecture of mouse and human antibody repertoires is defined by the sequence similarity networks of the clones that compose them. The major principles that define the architecture of antibody repertoires have remained largely unknown. Here, we...
Ovalbumin Peptide Library Muramidase Immunization Amino Acid Motifs Humans B-Lymphocytes Hepatitis B Surface Antigens Clone Cells Datasets as Topic Neural Networks, Computer Single-Chain Antibodies Animals Antigens Mice
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Distribution based Fuzzy Estimate Spectral Clustering for Cancer Detection with Protein Sequence and Structural Motifs.

Asian Pacific journal of cancer prevention : APJCP Jul 27, 2018
Objective: In biological data analysis, protein sequence and structural motifs are an amino-acid sequence patterns that are widespread and used as tools for detecting the cancer at an earlier stage. To improve the cancer detection with minimum space ...
Humans Algorithms Biomarkers, Tumor Neoplasms Fuzzy Logic Cluster Analysis Amino Acid Motifs
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High-Order Convolutional Neural Network Architecture for Predicting DNA-Protein Binding Sites.

IEEE/ACM transactions on computational biology and bioinformatics Mar 26, 2018
Although Deep learning algorithms have outperformed conventional methods in predicting the sequence specificities of DNA-protein binding, they lack to consider the dependencies among nucleotides and the diverse binding lengths for different transcrip...
DNA DNA-Binding Proteins Binding Sites Amino Acid Motifs Chromatin Immunoprecipitation Genomics Computational Biology Transcription Factors Area Under Curve Software Algorithms Protein Binding Neural Networks, Computer
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Computational Prediction of Sigma-54 Promoters in Bacterial Genomes by Integrating Motif Finding and Machine Learning Strategies.

IEEE/ACM transactions on computational biology and bioinformatics Mar 15, 2018
Sigma factor, as a unit of RNA polymerase holoenzyme, is a critical factor in the process of gene transcriptional regulation. It recognizes the specific DNA sites and brings the core enzyme of RNA polymerase to the upstream regions of target genes. T...
Escherichia coli Models, Statistical Escherichia coli Proteins Base Sequence Machine Learning Software Reproducibility of Results Amino Acid Motifs False Positive Reactions Computational Biology DNA-Directed RNA Polymerases Promoter Regions, Genetic RNA Polymerase Sigma 54 Transcription, Genetic Genome, Bacterial
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Prediction of GPCR-Ligand Binding Using Machine Learning Algorithms.

Computational and mathematical methods in medicine Jan 30, 2018
We propose a novel method that predicts binding of G-protein coupled receptors (GPCRs) and ligands. The proposed method uses hub and cycle structures of ligands and amino acid motif sequences of GPCRs, rather than the 3D structure of a receptor or si...
Receptors, G-Protein-Coupled Area Under Curve False Positive Reactions Algorithms Quercetin Humans Binding Sites Reproducibility of Results Ligands Machine Learning Amino Acid Motifs ROC Curve Software Sequence Analysis, Protein Protein Binding
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