AIMC Topic: Models, Genetic

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Deep Learning Benchmarks on L1000 Gene Expression Data.

IEEE/ACM transactions on computational biology and bioinformatics Dec 8, 2020
Gene expression data can offer deep, physiological insights beyond the static coding of the genome alone. We believe that realizing this potential requires specialized, high-capacity machine learning methods capable of using underlying biological str...
Humans Algorithms Gene Expression Profiling Computational Biology Models, Genetic Databases, Genetic Cell Line Transcriptome Deep Learning Protein Interaction Maps
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CGINet: graph convolutional network-based model for identifying chemical-gene interaction in an integrated multi-relational graph.

BMC bioinformatics Nov 26, 2020
BACKGROUND: Elucidation of interactive relation between chemicals and genes is of key relevance not only for discovering new drug leads in drug development but also for repositioning existing drugs to novel therapeutic targets. Recently, biological n...
Area Under Curve Epistasis, Genetic Humans Neural Networks, Computer Gene Regulatory Networks Algorithms Models, Genetic
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Transforming the study of organisms: Phenomic data models and knowledge bases.

PLoS computational biology Nov 24, 2020
The rapidly decreasing cost of gene sequencing has resulted in a deluge of genomic data from across the tree of life; however, outside a few model organism databases, genomic data are limited in their scientific impact because they are not accompanie...
Phenomics Semantics Classification Gene-Environment Interaction Computational Biology Models, Genetic Databases, Genetic Models, Statistical Models, Biological Knowledge Bases Phenotype Animals Ecosystem Humans
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Genome-enabled prediction of reproductive traits in Nellore cattle using parametric models and machine learning methods.

Animal genetics Nov 16, 2020
This study aimed to assess the predictive ability of different machine learning (ML) methods for genomic prediction of reproductive traits in Nellore cattle. The studied traits were age at first calving (AFC), scrotal circumference (SC), early pregna...
Machine Learning Phenotype Brazil Cattle Genomics Polymorphism, Single Nucleotide Pregnancy Female Animals Models, Genetic Reproduction
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Learning and interpreting the gene regulatory grammar in a deep learning framework.

PLoS computational biology Nov 2, 2020
Deep neural networks (DNNs) have achieved state-of-the-art performance in identifying gene regulatory sequences, but they have provided limited insight into the biology of regulatory elements due to the difficulty of interpreting the complex features...
Binding Sites Enhancer Elements, Genetic Genes, Regulator Gene Regulatory Networks Mice Computational Biology Databases, Genetic Terminology as Topic Models, Genetic Neural Networks, Computer Computer Simulation Transcription Factors Animals Deep Learning
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Development of a susceptibility gene based novel predictive model for the diagnosis of ulcerative colitis using random forest and artificial neural network.

Aging Oct 24, 2020
Ulcerative colitis is a type of inflammatory bowel disease characterized by chronic and recurrent nonspecific inflammation of the intestinal tract. To find susceptibility genes and develop a novel predictive model of ulcerative colitis, two sets of c...
Genetic Predisposition to Disease Models, Genetic Colitis, Ulcerative Humans Neural Networks, Computer Retrospective Studies
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Identification and Classification of Enhancers Using Dimension Reduction Technique and Recurrent Neural Network.

Computational and mathematical methods in medicine Oct 18, 2020
Enhancers are noncoding fragments in DNA sequences, which play an important role in gene transcription and translation. However, due to their high free scattering and positional variability, the identification and classification of enhancers have a h...
Support Vector Machine Algorithms Humans Enhancer Elements, Genetic Neural Networks, Computer Computational Biology Databases, Genetic Mathematical Concepts Machine Learning Models, Genetic Base Sequence Base Composition
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Implementing logical inference based on DNA assembly.

Bio Systems Oct 14, 2020
Algorithms and information processing, fundamental to biological system, are an essential aspect of many elementary physical phenomena, such as molecular self-assembly. Self-assembly system has been proved to be capable of performing many logic opera...
Models, Genetic DNA Artificial Intelligence Logic Software Algorithms
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Predicting 3D genome folding from DNA sequence with Akita.

Nature methods Oct 12, 2020
In interphase, the human genome sequence folds in three dimensions into a rich variety of locus-specific contact patterns. Cohesin and CTCF (CCCTC-binding factor) are key regulators; perturbing the levels of either greatly disrupts genome-wide foldin...
Cell Cycle Proteins CCCTC-Binding Factor Chromosomal Proteins, Non-Histone Humans Cohesins DNA-Binding Proteins Neural Networks, Computer Models, Genetic Gene Expression Regulation Sequence Analysis, DNA Genome, Human
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DeepC: predicting 3D genome folding using megabase-scale transfer learning.

Nature methods Oct 12, 2020
Predicting the impact of noncoding genetic variation requires interpreting it in the context of three-dimensional genome architecture. We have developed deepC, a transfer-learning-based deep neural network that accurately predicts genome folding from...
Humans Neural Networks, Computer CCCTC-Binding Factor Base Sequence Computer Simulation Genome, Human Genomic Structural Variation Genomics Chromatin Models, Genetic
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