AIMC Topic: Genome, Human

Clear Filters Showing 71 to 80 of 198 articles

Cross-species regulatory sequence activity prediction.

PLoS computational biology Jul 20, 2020
Machine learning algorithms trained to predict the regulatory activity of nucleic acid sequences have revealed principles of gene regulation and guided genetic variation analysis. While the human genome has been extensively annotated and studied, mod...
Databases, Genetic Sequence Analysis, DNA Models, Statistical Computational Biology Epigenomics Models, Genetic Gene Expression Regulation Machine Learning Genome, Human Software Species Specificity Algorithms Quantitative Trait Loci Animals Mutation Mice Hepatocytes Genomics Genetic Variation Humans Neural Networks, Computer
View on PubMed DOI

Decoding whole-genome mutational signatures in 37 human pan-cancers by denoising sparse autoencoder neural network.

Oncogene Jun 11, 2020
Millions of somatic mutations have recently been discovered in cancer genomes. These mutations in cancer genomes occur due to internal and external mutagenesis forces. Decoding the mutational processes by examining their unique patterns has successfu...
INDEL Mutation Point Mutation Deep Learning DNA Genome, Human Humans Neoplasms
View on PubMed DOI

Predicting geographic location from genetic variation with deep neural networks.

eLife Jun 8, 2020
Most organisms are more closely related to nearby than distant members of their species, creating spatial autocorrelations in genetic data. This allows us to predict the location of origin of a genetic sample by comparing it to a set of samples of kn...
Humans Genotype Plasmodium falciparum Genetic Variation Neural Networks, Computer Animals Genomics Anopheles Genome, Human Animal Distribution Demography
View on PubMed DOI

Acute myeloid leukemia and artificial intelligence, algorithms and new scores.

Best practice & research. Clinical haematology Jun 7, 2020
Artificial intelligence, and more narrowly machine-learning, is beginning to expand humanity's capacity to analyze increasingly large and complex datasets. Advances in computer hardware and software have led to breakthroughs in multiple sectors of ou...
Machine Learning Leukemia, Myeloid, Acute Human Genome Project Genome, Human Humans
View on PubMed DOI

Combining Supervised and Unsupervised Machine Learning Methods for Phenotypic Functional Genomics Screening.

SLAS discovery : advancing life sciences R & D May 13, 2020
There has been an increase in the use of machine learning and artificial intelligence (AI) for the analysis of image-based cellular screens. The accuracy of these analyses, however, is greatly dependent on the quality of the training sets used for bu...
High-Throughput Screening Assays Genome, Human Unsupervised Machine Learning RNA, Small Interfering Supervised Machine Learning Humans Phenotype Genomics
View on PubMed DOI

Opening the Black Box: Interpretable Machine Learning for Geneticists.

Trends in genetics : TIG Apr 17, 2020
Because of its ability to find complex patterns in high dimensional and heterogeneous data, machine learning (ML) has emerged as a critical tool for making sense of the growing amount of genetic and genomic data available. While the complexity of ML ...
Genetics, Medical Genome, Human Genetics, Population Humans Machine Learning Computational Biology
View on PubMed DOI

Mb-level CpG and TFBS islands visualized by AI and their roles in the nuclear organization of the human genome.

Genes & genetic systems Mar 12, 2020
Unsupervised machine learning that can discover novel knowledge from big sequence data without prior knowledge or particular models is highly desirable for current genome study. We previously established a batch-learning self-organizing map (BLSOM) f...
Centromere Chromosomes, Human Heterochromatin Humans Artificial Intelligence Protein Binding CpG Islands Transcription Factors Genome, Human Oligonucleotides Binding Sites
View on PubMed DOI

Exploring the Consistency of the Quality Scores with Machine Learning for Next-Generation Sequencing Experiments.

BioMed research international Feb 25, 2020
BACKGROUND: Next-generation sequencing enables massively parallel processing, allowing lower cost than the other sequencing technologies. In the subsequent analysis with the NGS data, one of the major concerns is the reliability of variant calls. Alt...
High-Throughput Nucleotide Sequencing Algorithms Genome, Human Humans Linear Models Reproducibility of Results Machine Learning Base Sequence Computational Biology Software
View on PubMed DOI

PANDA: Prioritization of autism-genes using network-based deep-learning approach.

Genetic epidemiology Feb 10, 2020
Understanding the genetic background of complex diseases and disorders plays an essential role in the promising precision medicine. The evaluation of candidate genes, however, requires time-consuming and expensive experiments given a large number of ...
Genome, Human Gene Regulatory Networks Genetic Association Studies Autistic Disorder Humans Deep Learning
View on PubMed DOI

Combined Use of Three Machine Learning Modeling Methods to Develop a Ten-Gene Signature for the Diagnosis of Ventilator-Associated Pneumonia.

Medical science monitor : international medical journal of experimental and clinical research Feb 7, 2020
BACKGROUND This study aimed to use three modeling methods, logistic regression analysis, random forest analysis, and fully-connected neural network analysis, to develop a diagnostic gene signature for the diagnosis of ventilator-associated pneumonia ...
Humans Machine Learning Algorithms Molecular Sequence Annotation Area Under Curve Gene Ontology Gene Expression Regulation Pneumonia, Ventilator-Associated Genome, Human Gene Expression Profiling Protein Interaction Maps Databases, Genetic
View on PubMed DOI
Popular Topics
Recent Journals