AIMC Topic: Saccharomyces cerevisiae
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iRNA-m5U: A sequence based predictor for identifying 5-methyluridine modification sites in Saccharomyces cerevisiae.
Methods (San Diego, Calif.)
Apr 18, 2021
The 5-methyluridine (mU)modification plays important roles in a series of biological processes. Accurate identification of mU sites will be helpful to decode its biological functions. Although experimental techniques have been proposed to detect mU, ...
A convolutional neural network for the prediction and forward design of ribozyme-based gene-control elements.
eLife
Apr 16, 2021
Ribozyme switches are a class of RNA-encoded genetic switch that support conditional regulation of gene expression across diverse organisms. An improved elucidation of the relationships between sequence, structure, and activity can improve our capaci...
Sequence Analysis, RNA
Models, Genetic
Escherichia coli
Structure-Activity Relationship
Machine Learning
Computer-Aided Design
Aptamers, Nucleotide
Saccharomyces cerevisiae
RNA, Catalytic
Neural Networks, Computer
Ligands
Base Sequence
High-Throughput Nucleotide Sequencing
Nucleic Acid Conformation
Gene Expression Regulation
Full-length ribosome density prediction by a multi-input and multi-output model.
PLoS computational biology
Mar 26, 2021
Translation elongation is regulated by a series of complicated mechanisms in both prokaryotes and eukaryotes. Although recent advance in ribosome profiling techniques has enabled one to capture the genome-wide ribosome footprints along transcripts at...
Machine learning applied for metabolic flux-based control of micro-aerated fermentations in bioreactors.
Biotechnology and bioengineering
Mar 17, 2021
Various bio-based processes depend on controlled micro-aerobic conditions to achieve a satisfactory product yield. However, the limiting oxygen concentration varies according to the micro-organism employed, while for industrial applications, there is...
Identification of RNA pseudouridine sites using deep learning approaches.
PloS one
Feb 23, 2021
Pseudouridine(Ψ) is widely popular among various RNA modifications which have been confirmed to occur in rRNA, mRNA, tRNA, and nuclear/nucleolar RNA. Hence, identifying them has vital significance in academic research, drug development and gene thera...
Deep learning the collisional cross sections of the peptide universe from a million experimental values.
Nature communications
Feb 19, 2021
The size and shape of peptide ions in the gas phase are an under-explored dimension for mass spectrometry-based proteomics. To investigate the nature and utility of the peptide collisional cross section (CCS) space, we measure more than a million dat...
A deep learning framework combined with word embedding to identify DNA replication origins.
Scientific reports
Jan 12, 2021
The DNA replication influences the inheritance of genetic information in the DNA life cycle. As the distribution of replication origins (ORIs) is the major determinant to precisely regulate the replication process, the correct identification of ORIs ...
Optimal tuning of weighted kNN- and diffusion-based methods for denoising single cell genomics data.
PLoS computational biology
Jan 7, 2021
The analysis of single-cell genomics data presents several statistical challenges, and extensive efforts have been made to produce methods for the analysis of this data that impute missing values, address sampling issues and quantify and correct for ...
Graph embeddings on gene ontology annotations for protein-protein interaction prediction.
BMC bioinformatics
Dec 16, 2020
BACKGROUND: Protein-protein interaction (PPI) prediction is an important task towards the understanding of many bioinformatics functions and applications, such as predicting protein functions, gene-disease associations and disease-drug associations. ...
Deep learning suggests that gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure.
Nature communications
Dec 1, 2020
Understanding the genetic regulatory code governing gene expression is an important challenge in molecular biology. However, how individual coding and non-coding regions of the gene regulatory structure interact and contribute to mRNA expression leve...
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