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Saccharomyces cerevisiae

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DetecDiv, a generalist deep-learning platform for automated cell division tracking and survival analysis.

eLife
Automating the extraction of meaningful temporal information from sequences of microscopy images represents a major challenge to characterize dynamical biological processes. So far, strong limitations in the ability to quantitatively analyze single-c...

A deep learning framework for identifying essential proteins based on multiple biological information.

BMC bioinformatics
BACKGROUND: Essential Proteins are demonstrated to exert vital functions on cellular processes and are indispensable for the survival and reproduction of the organism. Traditional centrality methods perform poorly on complex protein-protein interacti...

Automation of yeast spot assays using an affordable liquid handling robot.

SLAS technology
The spot assay of the budding yeast Saccharomyces cerevisiae is an experimental method that is used to evaluate the effect of genotypes, medium conditions, and environmental stresses on cell growth and survival. Automation of the spot assay experimen...

Prediction of ethanol fermentation under stressed conditions using yeast morphological data.

Journal of bioscience and bioengineering
A high sugar concentration is used as a starting condition in alcoholic fermentation by budding yeast, which shows changes in intracellular state and cell morphology under conditions of high-sugar stress. In this study, we developed artificial intell...

MM-StackEns: A new deep multimodal stacked generalization approach for protein-protein interaction prediction.

Computers in biology and medicine
Accurate in-silico identification of protein-protein interactions (PPIs) is a long-standing problem in biology, with important implications in protein function prediction and drug design. Current computational approaches predominantly use a single da...

DeepDetect: Deep Learning of Peptide Detectability Enhanced by Peptide Digestibility and Its Application to DIA Library Reduction.

Analytical chemistry
In tandem mass spectrometry-based proteomics, proteins are digested into peptides by specific protease(s), but generally only a fraction of peptides can be detected. To characterize detectable proteotypic peptides, we have developed a series of metho...

SGPPI: structure-aware prediction of protein-protein interactions in rigorous conditions with graph convolutional network.

Briefings in bioinformatics
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...

Prediction of Multiple Types of RNA Modifications via Biological Language Model.

IEEE/ACM transactions on computational biology and bioinformatics
It has been demonstrated that RNA modifications play essential roles in multiple biological processes. Accurate identification of RNA modifications in the transcriptome is critical for providing insights into the biological functions and mechanisms. ...

Is AI essential? Examining the need for deep learning in image-activated sorting of .

Lab on a chip
Artificial intelligence (AI) has become a focal point across a multitude of societal sectors, with science not being an exception. Particularly in the life sciences, imaging flow cytometry has increasingly integrated AI for automated management and c...

Prediction of Protein-Protein Interactions Using Vision Transformer and Language Model.

IEEE/ACM transactions on computational biology and bioinformatics
The knowledge of protein-protein interaction (PPI) helps us to understand proteins' functions, the causes and growth of several diseases, and can aid in designing new drugs. The majority of existing PPI research has relied mainly on sequence-based ap...