Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Jan 1, 2018
Machine Learning (ML) methods are now influencing major decisions about patient care, new medical methods, drug development and their use and importance are rapidly increasing in all areas. However, these ML methods are inherently complex and often d...
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Jan 1, 2018
As the bioinformatics field grows, it must keep pace not only with new data but with new algorithms. Here we contribute a thorough analysis of 13 state-of-the-art, commonly used machine learning algorithms on a set of 165 publicly available classific...
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Jan 1, 2018
Our knowledge of the biological mechanisms underlying complex human disease is largely incomplete. While Semantic Web technologies, such as the Web Ontology Language (OWL), provide powerful techniques for representing existing knowledge, well-establi...
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Jan 1, 2018
Electronic Health Records (EHRs) contain a wealth of patient data useful to biomedical researchers. At present, both the extraction of data and methods for analyses are frequently designed to work with a single snapshot of a patient's record. Health ...
Journal of the American Medical Informatics Association : JAMIA
Jan 1, 2018
OBJECTIVE: Data integration methods that combine data from different molecular levels such as genome, epigenome, transcriptome, etc., have received a great deal of interest in the past few years. It has been demonstrated that the synergistic effects ...
Xi bao yu fen zi mian yi xue za zhi = Chinese journal of cellular and molecular immunology
Dec 1, 2017
Objective To screen the nucleus located-methyltransferase in murine macrophages (RAW246.7 cells) after peroxisome proliferator-activated receptors (PPAR) is activated by alpinetin so as to prove the epigenetic modification effect of alpinetin. Method...
Current opinion in infectious diseases
Dec 1, 2017
PURPOSE OF REVIEW: Antimicrobial resistance (AMR) is a threat to global health and new approaches to combating AMR are needed. Use of machine learning in addressing AMR is in its infancy but has made promising steps. We reviewed the current literatur...
MOTIVATION: Our overall goal is to develop machine-learning approaches based on genomics and other relevant accessible information for use in predicting how a patient will respond to a given proposed drug or treatment. Given the complexity of this pr...
MOTIVATION: Deep neural network architectures such as convolutional and long short-term memory networks have become increasingly popular as machine learning tools during the recent years. The availability of greater computational resources, more data...
SUMMARY: As one of the most important tasks in protein sequence analysis, protein remote homology detection is critical for both basic research and practical applications. Here, we present an effective web server for protein remote homology detection...
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