The Reactome project builds, maintains, and publishes a knowledgebase of biological pathways. The information in the knowledgebase is gathered from the experts in the field, peer reviewed and edited by Reactome editorial staff, and then published to ...
Elucidating the effects of naturally occurring genetic variation is one of the major challenges for personalized health and personalized medicine. Here, we introduce SNAP2, a novel neural network based classifier that improves over the state-of-the-a...
MOTIVATION: Molecular recognition of N-terminal targeting peptides is the most common mechanism controlling the import of nuclear-encoded proteins into mitochondria and chloroplasts. When experimental information is lacking, computational methods can...
MOTIVATION: Target characterization for a biochemical network is a heuristic evaluation process that produces a characterization model that may aid in predicting the suitability of each molecule for drug targeting. These approaches are typically used...
An ontology-driven safe food consumption mobile system is considered. Over 3,000 compounds are being added to processed food, with numerous effects on the food: to add color, stabilize, texturize, preserve, sweeten, thicken, add flavor, soften, emuls...
OBJECTIVE: Assessment of medical trainee learning through pre-defined competencies is now commonplace in schools of medicine. We describe a novel electronic advisor system using natural language processing (NLP) to identify two geriatric medicine com...
As healthcare shifts from the hospital to the home, it is becoming increasingly important to understand how patients interact with home medical devices, to inform the safe and patient-friendly design of these devices. Distributed Cognition (DCog) has...
Biomedical ontologies are a critical component in biomedical research and practice. As an ontology evolves, its structure and content change in response to additions, deletions and updates. When editing a biomedical ontology, small local updates may ...
Journal of chemical information and modeling
Jun 2, 2015
Support vector machines (SVMs) are among the preferred machine learning algorithms for virtual compound screening and activity prediction because of their frequently observed high performance levels. However, a well-known conundrum of SVMs (and other...
Active participation and the highest level of independence during daily living are primary goals in neurorehabilitation. Therefore, standing and walking are key factors in many rehabilitation programs. Despite inconclusive evidence considering the be...
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