AIMC Topic: Evolution, Molecular

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Prediction of essential genes in prokaryote based on artificial neural network.

Genes & genomics Nov 17, 2019
BACKGROUND: Rapid identification of new essential genes is necessary to understand biological mechanisms and identify potential targets for antimicrobial drugs. Many computational methods have been proposed.
Neural Networks, Computer Algorithms Predictive Value of Tests Genes, Essential Bacterial Proteins Bacteria Computational Biology Evolution, Molecular
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PolyCRACKER, a robust method for the unsupervised partitioning of polyploid subgenomes by signatures of repetitive DNA evolution.

BMC genomics Jul 12, 2019
BACKGROUND: Our understanding of polyploid genomes is limited by our inability to definitively assign sequences to a specific subgenome without extensive prior knowledge like high resolution genetic maps or genome sequences of diploid progenitors. In...
Repetitive Sequences, Nucleic Acid Genome, Plant DNA, Plant Polyploidy Phylogeny Genomics Evolution, Molecular Unsupervised Machine Learning Triticum Nicotiana
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Coupling dynamics and evolutionary information with structure to identify protein regulatory and functional binding sites.

Proteins Jun 22, 2019
Binding sites in proteins can be either specifically functional binding sites (active sites) that bind specific substrates with high affinity or regulatory binding sites (allosteric sites), that modulate the activity of functional binding sites throu...
Humans Protein Binding Evolution, Molecular Proteins Artificial Intelligence Machine Learning Algorithms Binding Sites Allosteric Site Allosteric Regulation Databases, Protein Molecular Dynamics Simulation Protein Conformation
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DP-BINDER: machine learning model for prediction of DNA-binding proteins by fusing evolutionary and physicochemical information.

Journal of computer-aided molecular design May 23, 2019
DNA-binding proteins (DBPs) participate in various biological processes including DNA replication, recombination, and repair. In the human genome, about 6-7% of these proteins are utilized for genes encoding. DBPs shape the DNA into a compact structu...
Binding Sites Position-Specific Scoring Matrices Databases, Protein DNA DNA-Binding Proteins Humans Machine Learning Algorithms Animals Support Vector Machine Evolution, Molecular
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Beyond multidrug resistance: Leveraging rare variants with machine and statistical learning models in Mycobacterium tuberculosis resistance prediction.

EBioMedicine Apr 29, 2019
BACKGROUND: The diagnosis of multidrug resistant and extensively drug resistant tuberculosis is a global health priority. Whole genome sequencing of clinical Mycobacterium tuberculosis isolates promises to circumvent the long wait times and limited s...
Humans Machine Learning Prognosis Reproducibility of Results Microbial Sensitivity Tests Antitubercular Agents ROC Curve Tuberculosis, Multidrug-Resistant Genetic Variation Mycobacterium tuberculosis Genome, Bacterial Genomics Extensively Drug-Resistant Tuberculosis Cluster Analysis Computational Biology Models, Statistical Databases, Genetic Evolution, Molecular
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End-to-End Differentiable Learning of Protein Structure.

Cell systems Apr 17, 2019
Predicting protein structure from sequence is a central challenge of biochemistry. Co-evolution methods show promise, but an explicit sequence-to-structure map remains elusive. Advances in deep learning that replace complex, human-designed pipelines ...
Evolution, Molecular Protein Folding Sequence Analysis, Protein Machine Learning Software
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Evolutionarily informed deep learning methods for predicting relative transcript abundance from DNA sequence.

Proceedings of the National Academy of Sciences of the United States of America Mar 6, 2019
Deep learning methodologies have revolutionized prediction in many fields and show potential to do the same in molecular biology and genetics. However, applying these methods in their current forms ignores evolutionary dependencies within biological ...
Gene Expression Regulation Base Sequence Transcription, Genetic Sequence Analysis, DNA Evolution, Molecular Deep Learning DNA Models, Theoretical
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Robust optimization through neuroevolution.

PloS one Mar 1, 2019
We propose a method for evolving neural network controllers robust with respect to variations of the environmental conditions (i.e. that can operate effectively in new conditions immediately, without the need to adapt to variations). The method speci...
Evolution, Molecular Gene-Environment Interaction Neural Networks, Computer Models, Theoretical
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Levels and building blocks-toward a domain granularity framework for the life sciences.

Journal of biomedical semantics Jan 28, 2019
BACKGROUND: With the emergence of high-throughput technologies, Big Data and eScience, the use of online data repositories and the establishment of new data standards that require data to be computer-parsable become increasingly important. As a conse...
Evolution, Molecular Biological Science Disciplines Epithelium Biological Ontologies Cell Membrane
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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...
Proto-Oncogene Proteins c-mdm2 Models, Molecular Tumor Suppressor Protein p53 Mutation Machine Learning Thermodynamics Computational Biology Protein Domains Binding, Competitive Protein Binding Evolution, Molecular Proteins
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