bioinformatics proteomics

1. Bioinformatics for Proteomics Proteins govern most biological processes and functions. Recently, much attention has been paid to study the entire protein sets available in a cell. The term "proteome", a portmanteau of protein and genome, was coined by Marc Wilkins in 1994 and broadly defined as the total set of proteins that could be expressed in a sample or organism at a given time or the set of proteins that can be detected by some method. This varies with time and distinct requirements, or stresses. The related term ''proteomics'' was originally coined by Marc Wilkins and colleagues and is now widely identified as one of the omics- the set of post-genomic technologies which seek to further understand the genome in the molecules it encodes, their functions, interactions and connected properties. roteomics is an interdisciplinary domain which has benefited a lot from the genetic information of the Human Genome Project (HGP); it is also arising scientific research and exploration of proteomes from the complete level of intracellular protein composition, structure, and its own singular activity patterns. It is a valuable component of functional genomics. Proteomics research involves the separation, identification, qualitative, quantitative, and functional characterization of the entire protein profile of a given cell, tissue, and/or organism. Studying proteome also includes the profiling of isoforms, mutants, post-translational modifications, splice variants and protein-protein interactions. In this process, bioinformatics methods play a vital role for the analysis of proteomics. Applications for bioinformatics in proteomics research include: Diabetes research Tumor metastasis Nutrition research Fetal and maternal medicine

2. Renal disease diagnosis Neurology Urological cancer research Antibody profiling for study and treatment disease With years’ experience in advanced experiment equipments, Creative Proteomics can provide the following bioinformatics services in proteomics: Functional annotation and enrichment analysis Clustering analysis Network analysis Statistical analysis Proteomic analysis of post-translational modifications Standard analysis pipeline for identified proteins by MS/NMR results: Functional annotation (GO, KEGG, COG) Statistical analysis (volcano plot, veen plot, etc.) Enrichment analysis (GO, KEGG) Clustering analysis Protein-protein interactions analysis