Literature DB >> 27975225

Bioinformatics Tools for Proteomics Data Interpretation.

Karla Grisel Calderón-González1, Jesús Hernández-Monge2, María Esther Herrera-Aguirre1, Juan Pedro Luna-Arias3.   

Abstract

Biological systems function via intricate cellular processes and networks in which RNAs, metabolites, proteins and other cellular compounds have a precise role and are exquisitely regulated (Kumar and Mann, FEBS Lett 583(11):1703-1712, 2009). The development of high-throughput technologies, such as the Next Generation DNA Sequencing (NGS) and DNA microarrays for sequencing genomes or metagenomes, have triggered a dramatic increase in the last few years in the amount of information stored in the GenBank and UniProt Knowledgebase (UniProtKB). GenBank release 210, reported in October 2015, contains 202,237,081,559 nucleotides corresponding to 188,372,017 sequences, whilst there are only 1,222,635,267,498 nucleotides corresponding to 309,198,943 sequences from Whole Genome Shotgun (WGS) projects. In the case of UniProKB/Swiss-Prot, release 2015_12 (December 9, 2015) contains 196,219,159 amino acids that correspond to 550,116 entries. Meanwhile, UniProtKB/TrEMBL (release 2015_12 of December 9 2015) contains 1,838,851,8871 amino acids corresponding to 555,270,679 entries. Proteomics has also improved our knowledge of proteins that are being expressed in cells at a certain time of the cell cycle. It has also allowed the identification of molecules forming part of multiprotein complexes and an increasing number of posttranslational modifications (PTMs) that are present in proteins, as well as the variants of proteins expressed.

Entities:  

Keywords:  BioGRID; DAVID; Gene Ontology; HPRD; IPA; IntAct; Interactome mapping; KEGG; MINT; MPIDB; PANTHER; PIPs; Proteomics data interpretation; STRING; TAIR

Mesh:

Substances:

Year:  2016        PMID: 27975225     DOI: 10.1007/978-3-319-41448-5_16

Source DB:  PubMed          Journal:  Adv Exp Med Biol        ISSN: 0065-2598            Impact factor:   2.622


  6 in total

1.  Searching for Small Molecules with an Atomic Sort.

Authors:  Brendan M Duggan; Reiko Cullum; William Fenical; Luis A Amador; Abimael D Rodríguez; James J La Clair
Journal:  Angew Chem Int Ed Engl       Date:  2019-12-02       Impact factor: 15.336

2.  Presumed cancer-associated retinopathy (CAR) mimicking Sudden Acquired Retinal Degeneration Syndrome (SARDS) in canines.

Authors:  Sinisa D Grozdanic; Tatjana Lazic; Helga Kecova; Kabhilan Mohan; Grazyna Adamus; Markus H Kuehn
Journal:  Vet Ophthalmol       Date:  2020-12-27       Impact factor: 1.644

3.  Foodomics: Analytical Opportunities and Challenges.

Authors:  Alberto Valdés; Gerardo Álvarez-Rivera; Bárbara Socas-Rodríguez; Miguel Herrero; Elena Ibáñez; Alejandro Cifuentes
Journal:  Anal Chem       Date:  2021-11-23       Impact factor: 6.986

Review 4.  Metaproteomics insights into fermented fish and vegetable products and associated microbes.

Authors:  Emmanuel Sunday Okeke; Richard Ekeng Ita; Egong John Egong; Lydia Etuk Udofia; Chiamaka Linda Mgbechidinma; Otobong Donald Akan
Journal:  Food Chem (Oxf)       Date:  2021-10-22

Review 5.  Integration of Proteomics and Metabolomics in Exploring Genetic and Rare Metabolic Diseases.

Authors:  Michele Costanzo; Miriam Zacchia; Giuliana Bruno; Daniela Crisci; Marianna Caterino; Margherita Ruoppolo
Journal:  Kidney Dis (Basel)       Date:  2017-06-30

6.  Prognostic value and prospective molecular mechanism of miR-100-5p in hepatocellular carcinoma: A comprehensive study based on 1,258 samples.

Authors:  Qing-Lin He; Shan-Yu Qin; Lin Tao; Hong-Jian Ning; Hai-Xing Jiang
Journal:  Oncol Lett       Date:  2019-10-04       Impact factor: 2.967

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.