Neuro-proteomics and Neuro-systems Biology in the Quest of TBI Biomarker Discovery

2014 ◽  
pp. 3-41
Author(s):  
Ali Alawieh ◽  
Zahraa Sabra ◽  
Zhiqun Zhang ◽  
Firas Kobeissy ◽  
Kevin Wang
Keyword(s):  
Systems Biology ◽  
Biomarker Discovery

scholarly journals Systems Biology Modeling of the Radiation Sensitivity Network: A Biomarker Discovery Platform

2009 ◽  
Vol 75 (2) ◽  
pp. 497-505 ◽  
Author(s):  
Steven Eschrich ◽  
Hongling Zhang ◽  
Haiyan Zhao ◽  
David Boulware ◽  
Ji-Hyun Lee ◽  
...  
Keyword(s):  
Systems Biology ◽  
Biomarker Discovery ◽  
Radiation Sensitivity

scholarly journals An Integrative Approach to Assessing Diet–Cancer Relationships

Metabolites ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 123 ◽  
Author(s):  
Rachel Murphy
Keyword(s):  
Systems Biology ◽  
Health Professionals ◽  
Biomarker Discovery ◽  
Integrative Approach ◽  
Omics Data ◽  
The Public ◽  
The Past ◽  
Diet And Cancer ◽  
The Relationship ◽  
Considerable Body

The relationship between diet and cancer is often viewed with skepticism by the public and health professionals, despite a considerable body of evidence and general consistency in recommendations over the past decades. A systems biology approach which integrates ‘omics’ data including metabolomics, genetics, metagenomics, transcriptomics and proteomics holds promise for developing a better understanding of how diet affects cancer and for improving the assessment of diet through biomarker discovery thereby renewing confidence in diet–cancer links. This review discusses the application of multi-omics approaches to studies of diet and cancer. Considerations and challenges that need to be addressed to facilitate the investigation of diet–cancer relationships with multi-omic approaches are also discussed.

scholarly journals New frontiers in metabolomics: from measurement to insight

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 1148 ◽  
Author(s):  
Eli Riekeberg ◽  
Robert Powers
Keyword(s):  
Statistical Analysis ◽  
Systems Biology ◽  
Personalized Medicine ◽  
Rapid Growth ◽  
Health Research ◽  
Biomarker Discovery ◽  
Complete Analysis ◽  
Analysis Techniques ◽  
Measurement And Analysis ◽  
And Personalized Medicine

Metabolomics is the newest addition to the “omics” disciplines and has shown rapid growth in its application to human health research because of fundamental advancements in measurement and analysis techniques. Metabolomics has unique and proven advantages in systems biology and biomarker discovery. The next generation of analysis techniques promises even richer and more complete analysis capabilities that will enable earlier clinical diagnosis, drug refinement, and personalized medicine. A review of current advancements in methodologies and statistical analysis that are enhancing and improving the performance of metabolomics is presented along with highlights of some recent successful applications.

Computer Aided Knowledge Discovery in Biomedicine

2012 ◽  
pp. 1389-1403
Author(s):  
Vanathi Gopalakrishnan
Keyword(s):  
Protein Structure ◽  
Systems Biology ◽  
Knowledge Discovery ◽  
Structure Prediction ◽  
Biomarker Discovery ◽  
Protein Structure Determination ◽  
Mass Spectral ◽  
Computer Aided ◽  
And Function ◽  
Macromolecular Crystallization

This chapter provides a perspective on 3 important collaborative areas in systems biology research. These areas represent biological problems of clinical significance. The first area deals with macromolecular crystallization, which is a crucial step in protein structure determination. The second area deals with proteomic biomarker discovery from high-throughput mass spectral technologies; while the third area is protein structure prediction and complex fold recognition from sequence and prior knowledge of structure properties. For each area, successful case studies are revisited from the perspective of computer- aided knowledge discovery using machine learning and statistical methods. Information about protein sequence, structure, and function is slowly accumulating in standardized forms within databases. Methods are needed to maximize the use of this prior information for prediction and analysis purposes. This chapter provides insights into such methods by which available information in existing databases can be processed and combined with systems biology expertise to expedite biomedical discoveries.

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