AIMC Topic: Phenotype
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MAVE-NN: learning genotype-phenotype maps from multiplex assays of variant effect.
Genome biology
Apr 15, 2022
Multiplex assays of variant effect (MAVEs) are a family of methods that includes deep mutational scanning experiments on proteins and massively parallel reporter assays on gene regulatory sequences. Despite their increasing popularity, a general stra...
Machine learning models outperform deep learning models, provide interpretation and facilitate feature selection for soybean trait prediction.
BMC plant biology
Apr 8, 2022
Recent growth in crop genomic and trait data have opened opportunities for the application of novel approaches to accelerate crop improvement. Machine learning and deep learning are at the forefront of prediction-based data analysis. However, few app...
Phenotype-Based Threat Assessment.
Proceedings of the National Academy of Sciences of the United States of America
Apr 1, 2022
Bacterial pathogen identification, which is critical for human health, has historically relied on culturing organisms from clinical specimens. More recently, the application of machine learning (ML) to whole-genome sequences (WGSs) has facilitated pa...
PhenoRerank: A re-ranking model for phenotypic concept recognition pre-trained on human phenotype ontology.
Journal of biomedical informatics
Mar 26, 2022
The study aims at developing a neural network model to improve the performance of Human Phenotype Ontology (HPO) concept recognition tools. We used the terms, definitions, and comments about the phenotypic concepts in the HPO database to train our mo...
The Xenopus phenotype ontology: bridging model organism phenotype data to human health and development.
BMC bioinformatics
Mar 22, 2022
BACKGROUND: Ontologies of precisely defined, controlled vocabularies are essential to curate the results of biological experiments such that the data are machine searchable, can be computationally analyzed, and are interoperable across the biomedical...
DrABC: deep learning accurately predicts germline pathogenic mutation status in breast cancer patients based on phenotype data.
Genome medicine
Feb 25, 2022
BACKGROUND: Identifying breast cancer patients with DNA repair pathway-related germline pathogenic variants (GPVs) is important for effectively employing systemic treatment strategies and risk-reducing interventions. However, current criteria and ris...
Machine Learning analysis of high-grade serous ovarian cancer proteomic dataset reveals novel candidate biomarkers.
Scientific reports
Feb 23, 2022
Ovarian cancer is one of the most common gynecological malignancies, ranking third after cervical and uterine cancer. High-grade serous ovarian cancer (HGSOC) is one of the most aggressive subtype, and the late onset of its symptoms leads in most cas...
Machine Learning Identifies Pan-Cancer Landscape of Nrf2 Oxidative Stress Response Pathway-Related Genes.
Oxidative medicine and cellular longevity
Feb 17, 2022
BACKGROUND: Oxidative stress produced a large amount of reactive oxygen species (ROS), which played a pivotal role in balanced ability and determining cell fate. The activated Nrf2 signaling pathway that responds to the excessive ROS regulated the ex...
TCMPR: TCM Prescription Recommendation Based on Subnetwork Term Mapping and Deep Learning.
BioMed research international
Feb 17, 2022
Traditional Chinese medicine (TCM) has played an indispensable role in clinical diagnosis and treatment. Based on a patient's symptom phenotypes, computation-based prescription recommendation methods can recommend personalized TCM prescription using ...
Accurate and rapid prediction of tuberculosis drug resistance from genome sequence data using traditional machine learning algorithms and CNN.
Scientific reports
Feb 14, 2022
Effective and timely antibiotic treatment depends on accurate and rapid in silico antimicrobial-resistant (AMR) predictions. Existing statistical rule-based Mycobacterium tuberculosis (MTB) drug resistance prediction methods using bacterial genomic s...
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