AIMC Topic: Proteome

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Genome-Wide Detection and Analysis of Multifunctional Genes.

PLoS computational biology
Many genes can play a role in multiple biological processes or molecular functions. Identifying multifunctional genes at the genome-wide level and studying their properties can shed light upon the complexity of molecular events that underpin cellular...

Network fingerprint: a knowledge-based characterization of biomedical networks.

Scientific reports
It can be difficult for biomedical researchers to understand complex molecular networks due to their unfamiliarity with the mathematical concepts employed. To represent molecular networks with clear meanings and familiar forms for biomedical research...

GoFDR: A sequence alignment based method for predicting protein functions.

Methods (San Diego, Calif.)
In this study, we developed a method named GoFDR for predicting Gene Ontology (GO)-based protein functions. The input for GoFDR is simply a query sequence-based multiple sequence alignment (MSA) produced by PSI-BLAST. For each GO term annotated to th...

MetazSecKB: the human and animal secretome and subcellular proteome knowledgebase.

Database : the journal of biological databases and curation
The subcellular location of a protein is a key factor in determining the molecular function of the protein in an organism. MetazSecKB is a secretome and subcellular proteome knowledgebase specifically designed for metazoan, i.e. human and animals. Th...

Knowledge-Based Analysis for Detecting Key Signaling Events from Time-Series Phosphoproteomics Data.

PLoS computational biology
Cell signaling underlies transcription/epigenetic control of a vast majority of cell-fate decisions. A key goal in cell signaling studies is to identify the set of kinases that underlie key signaling events. In a typical phosphoproteomics study, phos...

ProCon - PROteomics CONversion tool.

Journal of proteomics
With the growing amount of experimental data produced in proteomics experiments and the requirements/recommendations of journals in the proteomics field to publicly make available data described in papers, a need for long-term storage of proteomics d...

Machine learning reveals sex-specific 17β-estradiol-responsive expression patterns in white perch (Morone americana) plasma proteins.

Proteomics
With growing abundance and awareness of endocrine disrupting compounds (EDCs) in the environment, there is a need for accurate and reliable detection of EDC exposure. Our objective in the present study was to observe differences within and between th...

Efficient prediction of progesterone receptor interactome using a support vector machine model.

International journal of molecular sciences
Protein-protein interaction (PPI) is essential for almost all cellular processes and identification of PPI is a crucial task for biomedical researchers. So far, most computational studies of PPI are intended for pair-wise prediction. Theoretically, p...

GlycoMine: a machine learning-based approach for predicting N-, C- and O-linked glycosylation in the human proteome.

Bioinformatics (Oxford, England)
MOTIVATION: Glycosylation is a ubiquitous type of protein post-translational modification (PTM) in eukaryotic cells, which plays vital roles in various biological processes (BPs) such as cellular communication, ligand recognition and subcellular reco...