Signal transduction and targeted therapy
Mar 14, 2023
AlphaFold2 (AF2) is an artificial intelligence (AI) system developed by DeepMind that can predict three-dimensional (3D) structures of proteins from amino acid sequences with atomic-level accuracy. Protein structure prediction is one of the most chal...
Role of memory in the function of biological tissues, organs and organisms remains unexplored with many unanswered questions. In this study, the emergence of associative memory in somatic (non-neural) tissues and its potential relation to tissue func...
The field of optimal experimental design uses mathematical techniques to determine experiments that are maximally informative from a given experimental setup. Here we apply a technique from artificial intelligence-reinforcement learning-to the optima...
BACKGROUND: In times of exponential data growth in the life sciences, machine-supported approaches are becoming increasingly important and with them the need for FAIR (Findable, Accessible, Interoperable, Reusable) and eScience-compliant data and met...
Journal of the Royal Society, Interface
Apr 6, 2022
Scientific results should not just be 'repeatable' (replicable in the same laboratory under identical conditions), but also 'reproducible' (replicable in other laboratories under similar conditions). Results should also, if possible, be 'robust' (rep...
This Perspective outlines recent progress and future directions for using machine learning (ML), a data-driven method, to address critical questions in the design, synthesis, processing, and characterization of . The achievement of these tasks requir...
Drug resistance updates : reviews and commentaries in antimicrobial and anticancer chemotherapy
Jan 28, 2022
Globally with over 10 million deaths per year, cancer is the most transversal disease across countries, cultures, and ethnicities, affecting both developed and developing regions. Tumorigenesis is dynamically altered by distinct events and can be let...
The expanding scale and inherent complexity of biological data have encouraged a growing use of machine learning in biology to build informative and predictive models of the underlying biological processes. All machine learning techniques fit models ...
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