AIMC Topic: Saccharomyces cerevisiae
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An Artificial Neural Network Assisted Dynamic Light Scattering Procedure for Assessing Living Cells Size in Suspension.
Sensors (Basel, Switzerland)
Jun 17, 2020
Dynamic light scattering (DLS) is an essential technique used for assessing the size of the particles in suspension, covering the range from nanometers to microns. Although it has been very well established for quite some time, improvement can still ...
Prediction of Protein-Protein Interactions with Local Weight-Sharing Mechanism in Deep Learning.
BioMed research international
Jun 13, 2020
Protein-protein interactions (PPIs) are important for almost all cellular processes, including metabolic cycles, DNA transcription and replication, and signaling cascades. The experimental methods for identifying PPIs are always time-consuming and ex...
Accurate prediction of species-specific 2-hydroxyisobutyrylation sites based on machine learning frameworks.
Analytical biochemistry
May 28, 2020
Lysine 2-hydroxyisobutyrylation (K) is a newly discovered post-translational modification (PTM) across eukaryotes and prokaryotes in recent years, which plays a significant role in diverse cellular functions. Accurate prediction of K sites is a first...
iMethyl-Deep: N6 Methyladenosine Identification of Yeast Genome with Automatic Feature Extraction Technique by Using Deep Learning Algorithm.
Genes
May 9, 2020
One of the most common and well studied post-transcription modifications in RNAs is N6-methyladenosine (m6A) which has been involved with a wide range of biological processes. Over the past decades, N6-methyladenosine produced some positive consequen...
Hierarchy and levels: analysing networks to study mechanisms in molecular biology.
Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Feb 24, 2020
Network representations are flat while mechanisms are organized into a hierarchy of levels, suggesting that the two are fundamentally opposed. I challenge this opposition by focusing on two aspects of the ways in which large-scale networks constructe...
MMPdb and MitoPredictor: Tools for facilitating comparative analysis of animal mitochondrial proteomes.
Mitochondrion
Jan 20, 2020
Data on experimentally-characterized animal mitochondrial proteomes (mt-proteomes) are limited to a few model organisms and are scattered across multiple databases, impeding a comparative analysis. We developed two resources to address these problems...
Identification of self-interacting proteins by integrating random projection classifier and finite impulse response filter.
BMC genomics
Dec 27, 2019
BACKGROUND: Identification of protein-protein interactions (PPIs) is crucial for understanding biological processes and investigating the cellular functions of genes. Self-interacting proteins (SIPs) are those in which more than two identical protein...
Multimodal deep representation learning for protein interaction identification and protein family classification.
BMC bioinformatics
Dec 2, 2019
BACKGROUND: Protein-protein interactions(PPIs) engage in dynamic pathological and biological procedures constantly in our life. Thus, it is crucial to comprehend the PPIs thoroughly such that we are able to illuminate the disease occurrence, achieve ...
Machine learning techniques for protein function prediction.
Proteins
Nov 14, 2019
Proteins play important roles in living organisms, and their function is directly linked with their structure. Due to the growing gap between the number of proteins being discovered and their functional characterization (in particular as a result of ...
Quantitative analysis of yeast fermentation process using Raman spectroscopy: Comparison of CARS and VCPA for variable selection.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Nov 11, 2019
Yeast is one of the most widely used microbial species in the field of microbiology, and it is crucial that rapid and accurate monitoring of its process. Therefore, this study presents a method using Raman spectroscopy for quantitative analysis of ye...
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