AIMC Topic: Saccharomyces cerevisiae
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Integrative approaches for predicting protein network perturbations through machine learning and structural characterization.
Journal of proteomics
May 30, 2025
Chromatin remodeling complexes, such as the Saccharomyces cerevisiae INO80 complex, exemplify how dynamic protein interaction networks govern cellular function through a balance of conserved structural modules and context-dependent functional partner...
A multi-objective evolutionary algorithm for detecting protein complexes in PPI networks using gene ontology.
Scientific reports
May 15, 2025
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
May 15, 2025
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...
Optimization process of coffee pulp wines combined with the artificial neural network and response surface methodology.
Scientific reports
May 14, 2025
Coffee pulp wine was made from coffee pulp. The level range of fermentation factors was determined by one-factor experiment. The significance factors affecting fermentation were screened by Plackett-Burman and steepest climbing experiments, which wer...
High throughput variant libraries and machine learning yield design rules for retron gene editors.
Nucleic acids research
Jan 11, 2025
The bacterial retron reverse transcriptase system has served as an intracellular factory for single-stranded DNA in many biotechnological applications. In these technologies, a natural retron non-coding RNA (ncRNA) is modified to encode a template fo...
Deep learning meets histones at the replication fork.
Cell
Sep 5, 2024
Epigenetic inheritance of heterochromatin requires transfer of parental H3-H4 tetramers to both daughter duplexes during replication. Three recent papers exploit yeast genetics coupled to inheritance assays and AlphaFold2-multimer predictions coupled...
A deep learning-guided automated workflow in LipidOz for detailed characterization of fungal fatty acid unsaturation by ozonolysis.
Journal of mass spectrometry : JMS
Sep 1, 2024
Understanding fungal lipid biology and metabolism is critical for antifungal target discovery as lipids play central roles in cellular processes. Nuances in lipid structural differences can significantly impact their functions, making it necessary to...
SGPPI: structure-aware prediction of protein-protein interactions in rigorous conditions with graph convolutional network.
Briefings in bioinformatics
Mar 19, 2023
While deep learning (DL)-based models have emerged as powerful approaches to predict protein-protein interactions (PPIs), the reliance on explicit similarity measures (e.g. sequence similarity and network neighborhood) to known interacting proteins m...
TransformerGO: predicting protein-protein interactions by modelling the attention between sets of gene ontology terms.
Bioinformatics (Oxford, England)
Apr 12, 2022
MOTIVATION: Protein-protein interactions (PPIs) play a key role in diverse biological processes but only a small subset of the interactions has been experimentally identified. Additionally, high-throughput experimental techniques that detect PPIs are...
DNAcycP: a deep learning tool for DNA cyclizability prediction.
Nucleic acids research
Apr 8, 2022
DNA mechanical properties play a critical role in every aspect of DNA-dependent biological processes. Recently a high throughput assay named loop-seq has been developed to quantify the intrinsic bendability of a massive number of DNA fragments simult...
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