Toward a next generation of predictive models: A systems biology primer

Food Control ◽  
2013 ◽  
Vol 29 (2) ◽  
pp. 336-342 ◽  
Author(s):  
J.F. Van Impe ◽  
D. Vercammen ◽  
E. Van Derlinden
Keyword(s):  
Systems Biology ◽  
Predictive Models ◽  
Next Generation

scholarly journals Developing next generation predictive models: a systems biology approach

2011 ◽  
Vol 1 ◽  
pp. 965-971 ◽  
Author(s):  
Jan F. Van Impe ◽  
Dominique Vercammen ◽  
Eva Van Derlinden
Keyword(s):  
Systems Biology ◽  
Predictive Models ◽  
Next Generation

Computational Systems Biology Perspective on Tuberculosis in Big Data Era

Web Services ◽  
2019 ◽  
pp. 2230-2254
Author(s):  
Amandeep Kaur Kahlon ◽  
Ashok Sharma
Keyword(s):  
Big Data ◽  
Systems Biology ◽  
Data Management ◽  
High Throughput ◽  
Predictive Models ◽  
System Biology ◽  
Prediction Models ◽  
Computational Systems Biology ◽  
Future Directions ◽  
Computational Systems

The major concern in this chapter is to understand the need of system biology in prediction models in studying tuberculosis infection in the big data era. The overall complexity of biological phenomenon, such as biochemical, biophysical, and other molecular processes, within pathogen as well as their interaction with host is studied through system biology approaches. First, consideration is given to the necessity of prediction models integrating system biology approaches and later on for their replacement and refinement using high throughput data. Various ongoing projects, consortium, databases, and research groups involved in tuberculosis eradication are also discussed. This chapter provides a brief account of TB predictive models and their importance in system biology to study tuberculosis and host-pathogen interactions. This chapter also addresses big data resources and applications, data management, limitations, challenges, solutions, and future directions.

Key strongylid nematodes of animals — Impact of next-generation transcriptomics on systems biology and biotechnology

2012 ◽  
Vol 30 (3) ◽  
pp. 469-488 ◽  
Author(s):  
Cinzia Cantacessi ◽  
Bronwyn E. Campbell ◽  
Robin B. Gasser
Keyword(s):  
Systems Biology ◽  
Next Generation

scholarly journals An engineering design approach to systems biology

2017 ◽  
Vol 9 (7) ◽  
pp. 574-583 ◽  
Author(s):  
Kevin A. Janes ◽  
Preethi L. Chandran ◽  
Roseanne M. Ford ◽  
Matthew J. Lazzara ◽  
Jason A. Papin ◽  
...  
Keyword(s):  
Systems Biology ◽  
Engineering Design ◽  
Predictive Models ◽  
Educational Philosophy ◽  
Design Approach ◽  
Engineering Approach

An engineering approach to systems biology applies educational philosophy, engineering design, and predictive models to solve contemporary problems in biomedicine.

scholarly journals Next Generation Protein Interactomes for Plant Systems Biology and Biomass Feedstock Research

2016 ◽  
Author(s):  
Joseph Robert Ecker ◽  
◽  
Shelly Trigg ◽  
Renee Garza ◽  
Haili Song ◽  
...  
Keyword(s):  
Systems Biology ◽  
Biomass Feedstock ◽  
Next Generation ◽  
Plant Systems Biology

scholarly journals Genetic approaches to study plant responses to environmental stresses

2018 ◽  
Author(s):  
Khaled Moustafa ◽  
Joanna M. Cross
Keyword(s):  
Gene Expression ◽  
Next Generation Sequencing ◽  
Systems Biology ◽  
Massively Parallel Sequencing ◽  
Environmental Stresses ◽  
Plant Responses ◽  
Rna Seq ◽  
Next Generation ◽  
Rnase Protection ◽  
Generation Sequencing

The assessment of gene expression levels is an important step toward elucidating gene functions temporally and spatially. Decades ago, typical studies were focusing on a few genes individually, whereas now researchers are able to examine whole genomes at once. The upgrade of throughput levels aided the introduction of systems biology approaches whereby cell functional networks can be scrutinized in their entireties to unravel potential functional interacting components. The birth of systems biology goes hand-in-hand with huge technological advancements and enables a fairly rapid detection of all transcripts in studied biological samples. Even so, earlier technologies that were restricted to probing single genes or a subset of genes still have their place in research laboratories. The objective here is to highlight key approaches used in gene expression analysis in plant responses to environmental stresses, or, more generally, any other condition of interest. Northern blots, RNase protection assays, and qPCR are described for their targeted detection of one or a few transcripts at a once. Differential display and serial analysis of gene expression represent non-targeted methods to evaluate expression changes of a significant number of gene transcripts. Finally, microarrays and RNA-seq (next-generation sequencing) contribute to the ultimate goal of identifying and quantifying all transcripts in a cell under conditions or stages of study. Recent examples of applications as well as principles, advantages, and drawbacks of each method are contrasted. We also suggest replacing the term "Next-Generation Sequencing (NGS)" with another less confusing synonym such as "RNA-seq", "high throughput sequencing", or "massively parallel sequencing" to avoid confusion with any future sequencing technologies.

scholarly journals Genetic approaches to study plant responses to environmental stresses

2018 ◽  
Author(s):  
Khaled Moustafa
Keyword(s):  
Gene Expression ◽  
Next Generation Sequencing ◽  
Systems Biology ◽  
Massively Parallel Sequencing ◽  
Environmental Stresses ◽  
Plant Responses ◽  
Rna Seq ◽  
Next Generation ◽  
Rnase Protection ◽  
Generation Sequencing

The assessment of gene expression levels is an important step toward elucidating gene functions temporally and spatially. Decades ago, typical studies were focusing on a few genes individually, whereas now researchers are able to examine whole genomes at once. The upgrade of throughput levels aided the introduction of systems biology approaches whereby cell functional networks can be scrutinized in their entireties to unravel potential functional interacting components. The birth of systems biology goes hand-in-hand with huge technological advancements and enables a fairly rapid detection of all transcripts in studied biological samples. Even so, earlier technologies that were restricted to probing single genes or a subset of genes still have their place in research laboratories. The objective here is to highlight key approaches used in gene expression analysis in plant responses to environmental stresses, or, more generally, any other condition of interest. Northern blots, RNase protection assays, and qPCR are described for their targeted detection of one or a few transcripts at a once. Differential display and serial analysis of gene expression represent non-targeted methods to evaluate expression changes of a significant number of gene transcripts. Finally, microarrays and RNA-seq (next-generation sequencing) contribute to the ultimate goal of identifying and quantifying all transcripts in a cell under conditions or stages of study. Recent examples of applications as well as principles, advantages, and drawbacks of each method are contrasted. We also suggest replacing the term "Next-Generation Sequencing (NGS)" with another less confusing synonym such as "RNA-seq", "high throughput sequencing", or "massively parallel sequencing" to avoid confusion with any future sequencing technologies.

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