AIMC Topic: Computational Biology

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Integrating bioinformatics and machine learning to identify glomerular injury genes and predict drug targets in diabetic nephropathy.

Scientific reports
Diabetes mellitus (DM) is a chronic metabolic disorder that poses significant challenges to public health. Among its various complications, diabetic nephropathy (DN) emerges as a critical microvascular complication associated with high mortality rate...

A multi-objective evolutionary algorithm for detecting protein complexes in PPI networks using gene ontology.

Scientific reports
Detecting protein complexes is crucial in computational biology for understanding cellular mechanisms and facilitating drug discovery. Evolutionary algorithms (EAs) have proven effective in uncovering protein complexes within networks of protein-prot...

Yeast Knowledge Graphs Database for Exploring Saccharomyces Cerevisiae and Schizosaccharomyces Pombe.

Journal of molecular biology
Biomedical literature contains an extensive wealth of information on gene and protein function across various biological processes and diseases. However, navigating this vast and often restricted-access data can be challenging, making it difficult to...

Meet the author: Hae Kyung Im.

Cell genomics
Hae Kyung Im's research group focuses on quantitative computational and statistical methods to tackle genomic data analysis and provides methods to translate the vast amount of genomic data for health research. In collaboration with Mengjie Chen's gr...

Identification of potential metabolic biomarkers and immune cell infiltration for metabolic associated steatohepatitis by bioinformatics analysis and machine learning.

Scientific reports
BACKGROUND: Metabolic associated steatohepatitis (MASH) represents a severe subtype of metabolic associated fatty liver disease (MASLD), with an increased risk of progression to cirrhosis and hepatocellular carcinoma. The nomenclature shift from nona...

Unraveling Disease-Associated PIWI-Interacting RNAs with a Contrastive Learning Methods.

Journal of chemical information and modeling
PIWI-interacting RNAs (piRNAs) are a class of small, non-coding RNAs predominantly expressed in the germ cells of animals and play a crucial role in maintaining genomic integrity, mediating transposon suppression, and ensuring gene stability. Beyond ...

NeuroPred-AIMP: Multimodal Deep Learning for Neuropeptide Prediction via Protein Language Modeling and Temporal Convolutional Networks.

Journal of chemical information and modeling
Neuropeptides are key signaling molecules that regulate fundamental physiological processes ranging from metabolism to cognitive function. However, accurate identification is a huge challenge due to sequence heterogeneity, obscured functional motifs ...

NetLnc: A Network-Based Computational Framework to Identify Immune Checkpoint-Related lncRNAs for Immunotherapy Response in Melanoma.

International journal of molecular sciences
Long non-coding RNAs (lncRNAs) could alter the tumor immune microenvironment and regulate the expression of immune checkpoints (ICPs) by regulating target genes in tumors. However, only a few lncRNAs have precise functions in immunity and potential f...

Exploring the potential biomarkers and potential causality of Ménière disease based on bioinformatics and machine learning.

Medicine
Meniere disease (MD) is a common inner ear disorder closely related to immune abnormalities, but research on the characteristic genes between MD and immune responses is still insufficient. We employ bioinformatics and machine learning to predict pote...