AIMC Topic: Saccharomyces cerevisiae

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Predicting epistasis across proteins by structural logic.

Proceedings of the National Academy of Sciences of the United States of America
Accurately predicting the phenotypic consequences of genetic variation is a major challenge for precision medicine. The problem is exacerbated by epistatic interactions, nonadditive effects between genetic variants that produce unexpected phenotypes....

Deep learning reveals endogenous sterols as allosteric modulators of the GPCR-Gα interface.

eLife
Endogenous intracellular allosteric modulators of GPCRs remain largely unexplored, with limited binding and phenotype data available. This gap arises from the lack of robust computational methods for unbiased cavity identification, cavity-specific li...

An LLM-Based Tool for Automated Generation of 3D Model Organism Colony Simulations.

ACS synthetic biology
We present MicroVerse, a software application based on large language models (LLMs) designed to generate C# scripts simulating three-dimensional colonies of model organisms, including and , within the Unity platform. The system, which utilizes fine-...

AI-directed gene fusing prolongs the evolutionary half-life of synthetic gene circuits.

Science advances
Evolutionary instability is a persistent challenge in synthetic biology, often leading to the loss of heterologous gene expression over time. Here, we present STABLES, a gene fusion strategy that links a gene of interest (GOI) to an essential endogen...

A comprehensive benchmarking of adaptive sampling tools for nanopore sequencing.

Genome biology
BACKGROUND: Adaptive sampling is an emerging technology to enrich target reads while depleting unwanted reads during real-time nanopore sequencing. The application of different algorithms has spawned various tools for the determination of read reject...

Genome-scale prediction of gene ontology from mass fingerprints reveals new metabolic gene functions.

Life science alliance
Mass-based fingerprinting can characterize microorganisms; however, expansion of these methods to predict specific gene functions is lacking. Therefore, mass fingerprinting was developed to functionally profile a yeast knockout library. Matrix-assist...

YModPred: an interpretable prediction method for multi-type RNA modification sites in S. cerevisiae based on deep learning.

BMC biology
BACKGROUND: RNA post-transcriptional modifications involve the addition of chemical groups to RNA molecules or alterations to their local structure. These modifications can change RNA base pairing, affect thermal stability, and influence RNA folding,...

MESM: integrating multi-source data for high-accuracy protein-protein interactions prediction through multimodal language models.

BMC biology
BACKGROUND: Protein-protein interactions (PPIs) play a critical role in essential biological processes such as signal transduction, enzyme activity regulation, cytoskeletal structure, immune responses, and gene regulation. However, current methods ma...

YTK Display-and-Secrete: Screening for Optimal Protein Secretion Elements in .

ACS synthetic biology
Engineering yeast to secrete target proteins requires searching for optimal combinations of promoters and signal peptides so that genes can be composed that give a high expression and efficient secretion. Most methods for this involve laborious, one-...

The EMC acts as a chaperone for membrane proteins.

Nature communications
Structure formation of membrane proteins is error-prone and thus requires chaperones that oversee this essential process in cell biology. The ER membrane protein complex (EMC) is well-defined as a transmembrane domain (TMD) insertase. In this study, ...