AI Medical Compendium Topic:
Genomics

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Using deep learning to identify translational research in genomic medicine beyond bench to bedside.

Database : the journal of biological databases and curation
Tracking scientific research publications on the evaluation, utility and implementation of genomic applications is critical for the translation of basic research to impact clinical and population health. In this work, we utilize state-of-the-art mach...

Annotation of gene product function from high-throughput studies using the Gene Ontology.

Database : the journal of biological databases and curation
High-throughput studies constitute an essential and valued source of information for researchers. However, high-throughput experimental workflows are often complex, with multiple data sets that may contain large numbers of false positives. The repres...

Knowledge base toward understanding actionable alterations and realizing precision oncology.

International journal of clinical oncology
In Japan, the National Cancer Center and university hospitals have initiated next-generation sequencing-based in vitro diagnostic testing for cancer patients as a method of clinical sequencing. Based on the molecular alterations detected, physicians ...

Leveraging Multilayered "Omics" Data for Atopic Dermatitis: A Road Map to Precision Medicine.

Frontiers in immunology
Atopic dermatitis (AD) is a complex multifactorial inflammatory skin disease that affects ~280 million people worldwide. About 85% of AD cases begin in childhood, a significant portion of which can persist into adulthood. Moreover, a typical progress...

Disease comorbidity-guided drug repositioning: a case study in schizophrenia.

AMIA ... Annual Symposium proceedings. AMIA Symposium
UNLABELLED: The key to any computational drug repositioning is the availability of relevant data in machine-understandable format. While large amount of genetic, genomic and chemical data are publicly available, large-scale higher-level disease and d...

A Primer on Data Analytics in Functional Genomics: How to Move from Data to Insight?

Trends in biochemical sciences
High-throughput methodologies and machine learning have been central in developing systems-level perspectives in molecular biology. Unfortunately, performing such integrative analyses has traditionally been reserved for bioinformaticians. This is now...

Agronomic Linked Data (AgroLD): A knowledge-based system to enable integrative biology in agronomy.

PloS one
Recent advances in high-throughput technologies have resulted in a tremendous increase in the amount of omics data produced in plant science. This increase, in conjunction with the heterogeneity and variability of the data, presents a major challenge...

A primer on deep learning in genomics.

Nature genetics
Deep learning methods are a class of machine learning techniques capable of identifying highly complex patterns in large datasets. Here, we provide a perspective and primer on deep learning applications for genome analysis. We discuss successful appl...

Found In Translation: a machine learning model for mouse-to-human inference.

Nature methods
Cross-species differences form barriers to translational research that ultimately hinder the success of clinical trials, yet knowledge of species differences has yet to be systematically incorporated in the interpretation of animal models. Here we pr...

Computational prediction of inter-species relationships through omics data analysis and machine learning.

BMC bioinformatics
BACKGROUND: Antibiotic resistance and its rapid dissemination around the world threaten the efficacy of currently-used medical treatments and call for novel, innovative approaches to manage multi-drug resistant infections. Phage therapy, i.e., the us...