AI Medical Compendium Topic:
Genomics

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Mantis-ml: Disease-Agnostic Gene Prioritization from High-Throughput Genomic Screens by Stochastic Semi-supervised Learning.

American journal of human genetics
Access to large-scale genomics datasets has increased the utility of hypothesis-free genome-wide analyses. However, gene signals are often insufficiently powered to reach experiment-wide significance, triggering a process of laborious triaging of gen...

EXpectation Propagation LOgistic REgRession on permissioned blockCHAIN (ExplorerChain): decentralized online healthcare/genomics predictive model learning.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Predicting patient outcomes using healthcare/genomics data is an increasingly popular/important area. However, some diseases are rare and require data from multiple institutions to construct generalizable models. To address institutional d...

Graph- and rule-based learning algorithms: a comprehensive review of their applications for cancer type classification and prognosis using genomic data.

Briefings in bioinformatics
Cancer is well recognized as a complex disease with dysregulated molecular networks or modules. Graph- and rule-based analytics have been applied extensively for cancer classification as well as prognosis using large genomic and other data over the p...

Deep-learning approach to identifying cancer subtypes using high-dimensional genomic data.

Bioinformatics (Oxford, England)
MOTIVATION: Cancer subtype classification has the potential to significantly improve disease prognosis and develop individualized patient management. Existing methods are limited by their ability to handle extremely high-dimensional data and by the i...

Machine learning and its applications in plant molecular studies.

Briefings in functional genomics
The advent of high-throughput genomic technologies has resulted in the accumulation of massive amounts of genomic information. However, biologists are challenged with how to effectively analyze these data. Machine learning can provide tools for bette...

Integrating distal and proximal information to predict gene expression via a densely connected convolutional neural network.

Bioinformatics (Oxford, England)
MOTIVATION: Interactions among cis-regulatory elements such as enhancers and promoters are main driving forces shaping context-specific chromatin structure and gene expression. Although there have been computational methods for predicting gene expres...

The Genome3D Consortium for Structural Annotations of Selected Model Organisms.

Methods in molecular biology (Clifton, N.J.)
Genome3D consortium is a collaborative project involving protein structure prediction and annotation resources developed by six world-leading structural bioinformatics groups, based in the United Kingdom (namely Blundell, Murzin, Gough, Sternberg, Or...

[Artificial intelligence-guided precision medicine in hematological disorders].

[Rinsho ketsueki] The Japanese journal of clinical hematology
Precision medicine in oncology uses genomic data to provide the right intervention in the right patients at the right time. For this purpose, next-generation sequencing (NGS) is an indispensable tool. However, further innovations are necessary, inclu...

The Path to and Impact of Disease Recognition with AI.

IEEE pulse
The Process of rare disease identification by clinical geneticists is closely associated with the ability to correlate the phenotype of a patient with the relevant genetic syndromes. In order to perform this correlation, the phenotype has to be descr...