AIMC Topic: Machine Learning

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dRFEtools: dynamic recursive feature elimination for omics.

Bioinformatics (Oxford, England)
MOTIVATION: Advances in technology have generated larger omics datasets with potential applications for machine learning. In many datasets, however, cost and limited sample availability result in an excessively higher number of features as compared t...

Machine learning approach for the estimation of missing precipitation data: a case study of South Korea.

Water science and technology : a journal of the International Association on Water Pollution Research
Precipitation is one of the driving forces in water cycles, and it is vital for understanding the water cycle, such as surface runoff, soil moisture, and evapotranspiration. However, missing precipitation data at the observatory becomes an obstacle t...

Protein-ligand binding affinity prediction exploiting sequence constituent homology.

Bioinformatics (Oxford, England)
MOTIVATION: Molecular docking is a commonly used approach for estimating binding conformations and their resultant binding affinities. Machine learning has been successfully deployed to enhance such affinity estimations. Many methods of varying compl...

MLNGCF: circRNA-disease associations prediction with multilayer attention neural graph-based collaborative filtering.

Bioinformatics (Oxford, England)
MOTIVATION: CircRNAs play a critical regulatory role in physiological processes, and the abnormal expression of circRNAs can mediate the processes of diseases. Therefore, exploring circRNAs-disease associations is gradually becoming an important area...

Bayesian multitask learning for medicine recommendation based on online patient reviews.

Bioinformatics (Oxford, England)
MOTIVATION: We propose a drug recommendation model that integrates information from both structured data (patient demographic information) and unstructured texts (patient reviews). It is based on multitask learning to predict review ratings of severa...

XGDAG: explainable gene-disease associations via graph neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: Disease gene prioritization consists in identifying genes that are likely to be involved in the mechanisms of a given disease, providing a ranking of such genes. Recently, the research community has used computational methods to uncover u...

Exploitation of surrogate variables in random forests for unbiased analysis of mutual impact and importance of features.

Bioinformatics (Oxford, England)
MOTIVATION: Random forest is a popular machine learning approach for the analysis of high-dimensional data because it is flexible and provides variable importance measures for the selection of relevant features. However, the complex relationships bet...

Validation of machine learning algorithms.

American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics

Design and Simulation of a Multilayer Chemical Neural Network That Learns via Backpropagation.

Artificial life
The design and implementation of adaptive chemical reaction networks, capable of adjusting their behavior over time in response to experience, is a key goal for the fields of molecular computing and DNA nanotechnology. Mainstream machine learning res...