Metabolomics

Gomase, Virendra; Changbhale, S.; Patil, Sunil A.; Kale, K. V.

doi:10.2174/138920008783331149

Cited by 59 publications

(49 citation statements)

References 71 publications

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“…This is being addressed by a few public and private spectral databases, such as the Human Metabolome Database (http://www.hmdb.ca), PubChem (pubchem.ncbi.nlm.nih.gov), the Madison Metabolomics Consortium Database, Metlin (http://metlin.scripps.edu), and the Chenomx database (4,29). In addition, unlike the information we have from the Human Genome Project, the number of endogenous metabolites that exist in the human metabolome is not known (29,62). Progress is being made in this area as databases are expanding (http://www.metabolomicssociety.org/ database.html) and metabolic pathway databases are available (Kyoto Encyclopedia of Genes and Genomes; http://www.…”

Section: Challenges and Future Directionsmentioning

confidence: 99%

The Emerging Field of Quantitative Blood Metabolomics for Biomarker Discovery in Critical Illnesses

Serkova

Standiford²,

Stringer

2011

Am J Respir Crit Care Med

166

124

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Metabolomics, a science of systems biology, is the global assessment of endogenous metabolites within a biologic system and represents a "snapshot" reading of gene function, enzyme activity, and the physiological landscape. Metabolite detection, either individual or grouped as a metabolomic profile, is usually performed in cells, tissues, or biofluids by either nuclear magnetic resonance spectroscopy or mass spectrometry followed by sophisticated multivariate data analysis. Because loss of metabolic homeostasis is common in critical illness, the metabolome could have many applications, including biomarker and drug target identification. Metabolomics could also significantly advance our understanding of the complex pathophysiology of acute illnesses, such as sepsis and acute lung injury/acute respiratory distress syndrome. Despite this potential, the clinical community is largely unfamiliar with the field of metabolomics, including the methodologies involved, technical challenges, and, most importantly, clinical uses. Although there is evidence of successful preclinical applications, the clinical usefulness and application of metabolomics in critical illness is just beginning to emerge, the advancement of which hinges on linking metabolite data to known and validated clinically relevant indices. In addition, other important aspects, such as patient selection, sample collection, and processing, as well as the needed multivariate data analysis, have to be taken into consideration before this innovative approach to biomarker discovery can become a reliable tool in the intensive care unit. The purpose of this review is to begin to familiarize clinicians with the field of metabolomics and its application for biomarker discovery in critical illnesses such as sepsis.

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Section: Challenges and Future Directionsmentioning

confidence: 99%

The Emerging Field of Quantitative Blood Metabolomics for Biomarker Discovery in Critical Illnesses

Serkova

Standiford²,

Stringer

2011

Am J Respir Crit Care Med

166

124

View full text Add to dashboard Cite

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“…In this research work antigenic epitopes of antigen protein from Eimeria acervulina is determined using the Gomase in 2007, Hopp and Woods, Bull & Breeze, Eisenberg, Chou & Fasman, and Levitt antigenicity [6][7][8]. The major histocompatibility complex (MHC) peptide binding of antigen protein is predicted using neural networks trained on C terminals of known epitopes.…”

Section: Methodsmentioning

confidence: 99%

“…Support Vector Machine (SVM) based method for prediction of promiscuous MHC class II binding peptides. SVM has been trained on the binary input of single amino acid sequence [9][10][11][12][13][14]. In addition, we predict those MHC ligands from whose C-terminal end is likely to be the result of proteosomal cleavage [15].…”

Section: Methodsmentioning

confidence: 99%

Eimeria acervulina ANALYSIS FOR BINDING PEPTIDES USING PROTEIN PROFILING FOR TARGET VALIDATION

VS¹,

RA²,

SS³

2010

Int J Mach Intell

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Abstract-Eimeria acervulina is a species of Eimeria that causes coccidiosis in older poultry. Lesions are limited to anterior or first third of the small intestine. Peptide fragments of antigen protein can be used to select nonamers for use in rational vaccine design and to increase the understanding of roles of the immune system in infectious diseases. Analysis shows MHC class II binding peptides of antigen protein from Eimeria acervulina are important determinant for protection of host form parasitic infection. In this assay, we used PSSM and SVM algorithms for antigen design and predicted the binding affinity of antigen protein having 299 amino acids, which shows 291 nonamers. Binding ability prediction of antigen peptides to major histocompatibility complex (MHC) class I & II molecules is important in vaccine development from Eimeria acervulina.

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“…Support Vector Machine (SVM) based method for prediction of promiscuous MHC class II binding peptides. SVM has been trained on the binary input of single amino acid sequence [6][7][8][9][10][11]. In addition, we predict those MHC ligands from whose Cterminal end is likely to be the result of proteosomal cleavage [12].…”

Section: Methodsmentioning

confidence: 99%

Proteomics approach for prediction of immunogenic site from Footand- mouth disease virus

VS¹,

AC²,

Tripathi³

2009

Int J of Biot Appl

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Abstract-Foot-and-mouth disease is caused by FMDV, an Aphthovirus of the viral family Picornaviridae. Peptide fragments of Foot-and-mouth disease virus protein can be used to select nonamers for use in rational vaccine design and to increase the understanding of roles of the immune system in infectious diseases. Analysis shows MHC class II binding peptides of protein from Footand-mouth disease virus are important determinant for protection of host form viral infection. In this assay we predicted the binding affinity of protein having 213 amino acids, which shows nonamers. These peptides are from a set of aligned peptides known to bind to a given MHC molecule as the predictor of MHC-peptide binding. MHCII molecules bind peptides in similar yet different modes and alignments of MHCII-ligands were obtained to be consistent with the binding mode of the peptides to their MHC class, this means the increase in affinity of MHC binding peptides may result in enhancement of immunogenicity of protein nonamers. Binding ability prediction of antigen peptides to major histocompatibility complex (MHC) class I & II molecules is important in vaccine development from Foot-and-mouth disease virus.

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Metabolomics

Cited by 59 publications

References 71 publications

The Emerging Field of Quantitative Blood Metabolomics for Biomarker Discovery in Critical Illnesses

The Emerging Field of Quantitative Blood Metabolomics for Biomarker Discovery in Critical Illnesses

Eimeria acervulina ANALYSIS FOR BINDING PEPTIDES USING PROTEIN PROFILING FOR TARGET VALIDATION

Proteomics approach for prediction of immunogenic site from Footand- mouth disease virus

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