Literature DB >> 16901220

Experimental standards for high-throughput proteomics.

Jason M Hogan1, Roger Higdon, Eugene Kolker.   

Abstract

Proteome analysis, utilizing high-throughput proteomics approaches, involves studying proteins that a whole organism (or specific tissue or cellular compartment) expresses under certain conditions. Intrinsic difficulties of these studies, as well as the enormous volumes of data they typically produce, make the proteome analysis and interpretation very difficult. As with any high-throughput approach, proteomics experiments should be carefully designed, analyzed, and verified. In addition to computational standards,experimental standards--simple and complex mixtures of known proteins--for high-throughput proteomics have to be developed and utilized. This article discusses such experimental standards and their implementations.

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Year:  2006        PMID: 16901220     DOI: 10.1089/omi.2006.10.152

Source DB:  PubMed          Journal:  OMICS        ISSN: 1536-2310


  9 in total

Review 1.  Standardization and omics science: technical and social dimensions are inseparable and demand symmetrical study.

Authors:  Christina Holmes; Fiona McDonald; Mavis Jones; Vural Ozdemir; Janice E Graham
Journal:  OMICS       Date:  2010-06

2.  Proteomic Analysis of the Human Anterior Pituitary Gland.

Authors:  Soujanya D Yelamanchi; Ankur Tyagi; Varshasnata Mohanty; Pinaki Dutta; Márta Korbonits; Sandip Chavan; Jayshree Advani; Anil K Madugundu; Gourav Dey; Keshava K Datta; M Rajyalakshmi; Nandini A Sahasrabuddhe; Abhishek Chaturvedi; Amit Kumar; Apabrita Ayan Das; Dhiman Ghosh; Gajendra M Jogdand; Haritha H Nair; Keshav Saini; Manoj Panchal; Mansi Ashwinsinh Sarvaiya; Soundappan S Mohanraj; Nabonita Sengupta; Priti Saxena; Pradeep Annamalai Subramani; Pradeep Kumar; Rakhil Akkali; Saraswatipura Vishwabrahmachar Reshma; Ramachandran Sarojini Santhosh; Sangita Rastogi; Sudarshan Kumar; Susanta Kumar Ghosh; Vamshi Krishna Irlapati; Anand Srinivasan; Bishan Das Radotra; Premendu P Mathur; G William Wong; Parthasarathy Satishchandra; Aditi Chatterjee; Harsha Gowda; Anil Bhansali; Akhilesh Pandey; Susarla K Shankar; Anita Mahadevan; T S Keshava Prasad
Journal:  OMICS       Date:  2018-12

3.  Design and initial characterization of the SC-200 proteomics standard mixture.

Authors:  Andrew Bauman; Roger Higdon; Sean Rapson; Brenton Loiue; Jason Hogan; Robin Stacy; Alberto Napuli; Wenjin Guo; Wesley van Voorhis; Jared Roach; Vincent Lu; Elizabeth Landorf; Elizabeth Stewart; Natali Kolker; Frank Collart; Peter Myler; Gerald van Belle; Eugene Kolker
Journal:  OMICS       Date:  2011-01-21

Review 4.  Personalized medicine beyond genomics: alternative futures in big data-proteomics, environtome and the social proteome.

Authors:  Vural Özdemir; Edward S Dove; Ulvi K Gürsoy; Semra Şardaş; Arif Yıldırım; Şenay Görücü Yılmaz; I Ömer Barlas; Kıvanç Güngör; Alper Mete; Sanjeeva Srivastava
Journal:  J Neural Transm (Vienna)       Date:  2015-12-08       Impact factor: 3.575

Review 5.  Challenges, current status and future perspectives of proteomics in improving understanding, diagnosis and treatment of vascular disease.

Authors:  J V Moxon; M P Padula; B R Herbert; J Golledge
Journal:  Eur J Vasc Endovasc Surg       Date:  2009-07-09       Impact factor: 7.069

Review 6.  The promise of multi-omics and clinical data integration to identify and target personalized healthcare approaches in autism spectrum disorders.

Authors:  Roger Higdon; Rachel K Earl; Larissa Stanberry; Caitlin M Hudac; Elizabeth Montague; Elizabeth Stewart; Imre Janko; John Choiniere; William Broomall; Natali Kolker; Raphael A Bernier; Eugene Kolker
Journal:  OMICS       Date:  2015-04

7.  Reproducible cancer biomarker discovery in SELDI-TOF MS using different pre-processing algorithms.

Authors:  Jinfeng Zou; Guini Hong; Xinwu Guo; Lin Zhang; Chen Yao; Jing Wang; Zheng Guo
Journal:  PLoS One       Date:  2011-10-14       Impact factor: 3.240

8.  Reproducibility and concordance of differential DNA methylation and gene expression in cancer.

Authors:  Chen Yao; Hongdong Li; Xiaopei Shen; Zheng He; Lang He; Zheng Guo
Journal:  PLoS One       Date:  2012-01-03       Impact factor: 3.240

9.  Learning from decoys to improve the sensitivity and specificity of proteomics database search results.

Authors:  Amit Kumar Yadav; Dhirendra Kumar; Debasis Dash
Journal:  PLoS One       Date:  2012-11-26       Impact factor: 3.240

  9 in total

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