AI Medical Compendium Topic:
Genomics

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[From genome analysis to construction of an integrated omics knowledgebase for crops].

Yi chuan = Hereditas
The advances in high-throughput technologies have enabled high-speed accumulation of omics data, which contain a large amount of genetic variations and their functional information. The integration and deep utilization of those data will be a long-te...

Maxwell®: An Unsupervised Learning Approach for 5P Medicine.

Studies in health technology and informatics
In the 5P medicine (Personalized, Preventive, Participative, Predictive and Pluri-expert), the general trend is to process data by displacing the barycenter of the information from hospital centered systems to the patient centered ones through his pe...

Promoter analysis and prediction in the human genome using sequence-based deep learning models.

Bioinformatics (Oxford, England)
MOTIVATION: Computational identification of promoters is notoriously difficult as human genes often have unique promoter sequences that provide regulation of transcription and interaction with transcription initiation complex. While there are many at...

Multi-omics integration-a comparison of unsupervised clustering methodologies.

Briefings in bioinformatics
With the recent developments in the field of multi-omics integration, the interest in factors such as data preprocessing, choice of the integration method and the number of different omics considered had increased. In this work, the impact of these f...

Computational functional genomics-based reduction of disease-related gene sets to their key components.

Bioinformatics (Oxford, England)
MOTIVATION: The genetic architecture of diseases becomes increasingly known. This raises difficulties in picking suitable targets for further research among an increasing number of candidates. Although expression based methods of gene set reduction a...

web-rMKL: a web server for dimensionality reduction and sample clustering of multi-view data based on unsupervised multiple kernel learning.

Nucleic acids research
More and more affordable high-throughput techniques for measuring molecular features of biomedical samples have led to a huge increase in availability and size of different types of multi-omic datasets, containing, for example, genetic or histone mod...

Deep learning: new computational modelling techniques for genomics.

Nature reviews. Genetics
As a data-driven science, genomics largely utilizes machine learning to capture dependencies in data and derive novel biological hypotheses. However, the ability to extract new insights from the exponentially increasing volume of genomics data requir...

Fair compute loads enabled by blockchain: sharing models by alternating client and server roles.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Decentralized privacy-preserving predictive modeling enables multiple institutions to learn a more generalizable model on healthcare or genomic data by sharing the partially trained models instead of patient-level data, while avoiding risk...