SIGNIFICANCE: Biomedical optics system design, image formation, and image analysis have primarily been guided by classical physical modeling and signal processing methodologies. Recently, however, deep learning (DL) has become a major paradigm in com...
Mathematical biosciences and engineering : MBE
Jan 25, 2022
It is prone to get stuck in a local minimum when solving the Traveling Salesman Problem (TSP) by the traditional Hopfield neural network (HNN) and hard to converge to an efficient solution, resulting from the defect of the penalty method used by the ...
Proceedings of the National Academy of Sciences of the United States of America
Jan 18, 2022
Inferotemporal (IT) cortex in humans and other primates is topographically organized, containing multiple hierarchically organized areas selective for particular domains, such as faces and scenes. This organization is commonly viewed in terms of evol...
MOTIVATION: Understanding chemical-gene interactions (CGIs) is crucial for screening drugs. Wet experiments are usually costly and laborious, which limits relevant studies to a small scale. On the contrary, computational studies enable efficient in-s...
Learning node representation is a fundamental problem in biological network analysis, as compact representation features reveal complicated network structures and carry useful information for downstream tasks such as link prediction and node classifi...
BACKGROUND: Human-machine teaming (HMT) typically combines perspectives from systems engineering, artificial intelligence (AI) and human-centered design (HCD), to achieve human systems integration (HSI) through the development of an integrative syste...
Network biology finds application in interpreting molecular interaction networks and providing insightful inferences using graph theoretical analysis of biological systems. The integration of computational biomodelling approaches with different hybri...
Journal of computational biology : a journal of computational molecular cell biology
Jan 1, 2022
We propose GRNUlar, a novel deep learning framework for supervised learning of gene regulatory networks (GRNs) from single-cell RNA-Sequencing (scRNA-Seq) data. Our framework incorporates two intertwined models. First, we leverage the expressive abil...
Combinatorial chemistry & high throughput screening
Jan 1, 2022
The modern pharmaceutical industry is transitioning from traditional methods to advanced technologies like artificial intelligence. In the current scenario, continuous efforts are being made to incorporate computational modeling and simulation in dru...
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