AIMC Topic: Algorithms

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A deep transfer learning-based protocol accelerates full quantum mechanics calculation of protein.

Briefings in bioinformatics
Effective full quantum mechanics (FQM) calculation of protein remains a grand challenge and of great interest in computational biology with substantial applications in drug discovery, protein dynamic simulation and protein folding. However, the huge ...

DeepHomo2.0: improved protein-protein contact prediction of homodimers by transformer-enhanced deep learning.

Briefings in bioinformatics
Protein-protein interactions play an important role in many biological processes. However, although structure prediction for monomer proteins has achieved great progress with the advent of advanced deep learning algorithms like AlphaFold, the structu...

RLBind: a deep learning method to predict RNA-ligand binding sites.

Briefings in bioinformatics
Identification of RNA-small molecule binding sites plays an essential role in RNA-targeted drug discovery and development. These small molecules are expected to be leading compounds to guide the development of new types of RNA-targeted therapeutics c...

Diachronic and synchronic variation in the performance of adaptive machine learning systems: the ethical challenges.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Machine learning (ML) has the potential to facilitate "continual learning" in medicine, in which an ML system continues to evolve in response to exposure to new data over time, even after being deployed in a clinical setting. In this arti...

Elucidating the functional roles of prokaryotic proteins using big data and artificial intelligence.

FEMS microbiology reviews
Annotating protein sequences according to their biological functions is one of the key steps in understanding microbial diversity, metabolic potentials, and evolutionary histories. However, even in the best-studied prokaryotic genomes, not all protei...

Deep-Learning Electron Diffractive Imaging.

Physical review letters
We report the development of deep-learning coherent electron diffractive imaging at subangstrom resolution using convolutional neural networks (CNNs) trained with only simulated data. We experimentally demonstrate this method by applying the trained ...

canSAR: update to the cancer translational research and drug discovery knowledgebase.

Nucleic acids research
canSAR (https://cansar.ai) is the largest public cancer drug discovery and translational research knowledgebase. Now hosted in its new home at MD Anderson Cancer Center, canSAR integrates billions of experimental measurements from across molecular pr...

IDEFE algorithm: IDE algorithm optimizes the fuzzy entropy for the gland segmentation.

Mathematical biosciences and engineering : MBE
Breast cancer occurs in the epithelial tissue of the gland, so the accuracy of gland segmentation is crucial to the physician's diagnosis. An innovative technique for breast mammography image gland segmentation is put forth in this paper. In the firs...

Hematology and Machine Learning.

The journal of applied laboratory medicine
BACKGROUND: Substantial improvements in computational power and machine learning (ML) algorithm development have vastly increased the limits of what autonomous machines are capable of. Since its beginnings in the 19th century, laboratory hematology h...