AIMC Topic: Machine Learning

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Machine learning-integrated omics for the risk and safety assessment of nanomaterials.

Biomaterials science
With the advancement in nanotechnology, we are experiencing transformation in world order with deep insemination of nanoproducts from basic necessities to advanced electronics, health care products and medicines. Therefore, nanoproducts, however, can...

Computational studies of anaplastic lymphoma kinase mutations reveal common mechanisms of oncogenic activation.

Proceedings of the National Academy of Sciences of the United States of America
Kinases play important roles in diverse cellular processes, including signaling, differentiation, proliferation, and metabolism. They are frequently mutated in cancer and are the targets of a large number of specific inhibitors. Surveys of cancer gen...

Integration and transfer learning of single-cell transcriptomes via cFIT.

Proceedings of the National Academy of Sciences of the United States of America
Large, comprehensive collections of single-cell RNA sequencing (scRNA-seq) datasets have been generated that allow for the full transcriptional characterization of cell types across a wide variety of biological and clinical conditions. As new methods...

Machine learning active-nematic hydrodynamics.

Proceedings of the National Academy of Sciences of the United States of America
Hydrodynamic theories effectively describe many-body systems out of equilibrium in terms of a few macroscopic parameters. However, such parameters are difficult to determine from microscopic information. Seldom is this challenge more apparent than in...

Early Prediction of Gestational Diabetes Mellitus in the Chinese Population via Advanced Machine Learning.

The Journal of clinical endocrinology and metabolism
CONTEXT: Accurate methods for early gestational diabetes mellitus (GDM) (during the first trimester of pregnancy) prediction in Chinese and other populations are lacking.

Inter classifier comparison to detect voice pathologies.

Mathematical biosciences and engineering : MBE
Voice pathologies are irregular vibrations produced due to vocal folds and various factors malfunctioning. In medical science, novel machine learning algorithms are applied to construct a system to identify disorders that occur invoice. This study ai...

The value of federated learning during and post-COVID-19.

International journal for quality in health care : journal of the International Society for Quality in Health Care
Federated learning (FL) as a distributed machine learning (ML) technique has lately attracted increasing attention of healthcare stakeholders as FL is perceived as a promising decentralized approach to address data privacy and security concerns. The ...

Machine learning approaches for elucidating the biological effects of natural products.

Natural product reports
Covering: 2000 to 2020 Machine learning (ML) is an efficient tool for the prediction of bioactivity and the study of structure-activity relationships. Over the past decade, an emerging trend for combining these approaches with the study of natural pr...

A machine-learning approach to map landscape connectivity in with genetic and environmental data.

Proceedings of the National Academy of Sciences of the United States of America
Mapping landscape connectivity is important for controlling invasive species and disease vectors. Current landscape genetics methods are often constrained by the subjectivity of creating resistance surfaces and the difficulty of working with interact...

Prediction of bio-sequence modifications and the associations with diseases.

Briefings in functional genomics
Modifications of protein, RNA and DNA play an important role in many biological processes and are related to some diseases. Therefore, accurate identification and comprehensive understanding of protein, RNA and DNA modification sites can promote rese...