AIMC Topic: Computational Biology

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Molecular structure and mechanism of protein MSMB, TPPP3, SPI1: Construction of novel 4 pancreatic cancer-related protein signatures model based on machine learning.

International journal of biological macromolecules
The high mortality rate of pancreatic cancer is closely related to its inconspicuous early symptoms and difficult diagnosis. In recent years, with the rapid development of proteomics and bioinformatics, the use of machine learning technology to analy...

scMDCL: A Deep Collaborative Contrastive Learning Framework for Matched Single-Cell Multiomics Data Clustering.

Journal of chemical information and modeling
Single-cell multiomics clustering integrates multiple omics data to analyze cellular heterogeneity and is crucial for uncovering complex biological processes and disease mechanisms. However, existing matched single-cell multiomics clustering methods ...

RBPsuite 2.0: an updated RNA-protein binding site prediction suite with high coverage on species and proteins based on deep learning.

BMC biology
BACKGROUND: RNA-binding proteins (RBPs) play crucial roles in many biological processes, and computationally identifying RNA-RBP interactions provides insights into the biological mechanism of diseases associated with RBPs.

Predicting the diversity of photosynthetic light-harvesting using thermodynamics and machine learning.

PLoS computational biology
Oxygenic photosynthesis is responsible for nearly all biomass production on Earth, and may have been a prerequisite for establishing a complex biosphere rich in multicellular life. Life on Earth has evolved to perform photosynthesis in a wide range o...

Biochemical Characterization of Disease-Associated Variants of Human Ornithine Transcarbamylase.

ACS chemical biology
Human ornithine transcarbamylase deficiency (OTCD) is the most common ureagenesis disorder in the world. OTCD is an X-linked genetic deficiency in which patients experience hyperammonemia to varying degrees depending on the severity of the genetic mu...

Cancer Drug Sensitivity Prediction Based on Deep Transfer Learning.

International journal of molecular sciences
In recent years, many approved drugs have been discovered using phenotypic screening, which elaborates the exact mechanisms of action or molecular targets of drugs. Drug susceptibility prediction is an important type of phenotypic screening. Large-sc...

Elucidating the role of KCTD10 in coronary atherosclerosis: Harnessing bioinformatics and machine learning to advance understanding.

Scientific reports
Atherosclerosis (AS) is increasingly recognized as a chronic inflammatory disease that significantly compromises vascular health and serves as a major contributor to cardiovascular diseases. KCTD10, a protein implicated in a variety of biological pro...

Comprehensive integration of diagnostic biomarker analysis and immune cell infiltration features in sepsis via machine learning and bioinformatics techniques.

Frontiers in immunology
INTRODUCTION: Sepsis, a critical medical condition resulting from an irregular immune response to infection, leads to life-threatening organ dysfunction. Despite medical advancements, the critical need for research into dependable diagnostic markers ...

BacTermFinder: a comprehensive and general bacterial terminator finder using a CNN ensemble.

NAR genomics and bioinformatics
A terminator is a DNA region that ends the transcription process. Currently, multiple computational tools are available for predicting bacterial terminators. However, these methods are specialized for certain bacteria or terminator type (i.e. intrins...

DeepMVD: A Novel Multiview Dynamic Feature Fusion Model for Accurate Protein Function Prediction.

Journal of chemical information and modeling
Proteins, as the fundamental macromolecules of life, play critical roles in various biological processes. Recent advancements in intelligent protein function prediction methods leverage sequences, structures, and biomedical literature data. Among the...