scholarly journals Biological network inference using low order partial correlation

Methods ◽  
2014 ◽  
Vol 69 (3) ◽  
pp. 266-273 ◽  
Author(s):  
Yiming Zuo ◽  
Guoqiang Yu ◽  
Mahlet G. Tadesse ◽  
Habtom W. Ressom
Keyword(s):  
Partial Correlation ◽  
Network Inference ◽  
Biological Network ◽  
Low Order

Biological network inference for drug discovery

2013 ◽  
Vol 18 (5-6) ◽  
pp. 256-264 ◽  
Author(s):  
Paola Lecca ◽  
Corrado Priami
Keyword(s):  
Drug Discovery ◽  
Network Inference ◽  
Biological Network

The Present and the Future Perspectives of Biological Network Inference

2011 ◽  
pp. 118-140 ◽  
Author(s):  
Paola Lecca ◽  
Alida Palmisano
Keyword(s):  
Reaction Kinetics ◽  
Network Structure ◽  
Network Inference ◽  
Biological Network ◽  
Reaction Pathway ◽  
Model Identification ◽  
Chemical Species ◽  
Kinetics Parameters ◽  
Common Opinion ◽  
Genomic Biology

Biological network inference is based on a series of studies and computational approaches to the deduction of the connectivity of chemical species, the reaction pathway, and the reaction kinetics of complex reaction systems from experimental measurements. Inference for network structure and reaction kinetics parameters governing the dynamics of a biological system is currently an active area of research. In the era of post-genomic biology, it is a common opinion among scientists that living systems (cells, tissues, organs and organisms) can be understood in terms of their network structure as well as in term of the evolution in time of this network structure. In this chapter, the authors make a survey of the recent methodologies proposed for the structure inference and for the parameter estimation of a system of interacting biological entities. Furthermore, they present the recent works of the authors about model identification and calibration.

scholarly journals The feasibility of genome-scale biological network inference using Graphics Processing Units

2017 ◽  
Vol 12 (1) ◽  
Author(s):  
Raghuram Thiagarajan ◽  
Amir Alavi ◽  
Jagdeep T. Podichetty ◽  
Jason N. Bazil ◽  
Daniel A. Beard
Keyword(s):  
Graphics Processing Units ◽  
Network Inference ◽  
Biological Network ◽  
Graphics Processing ◽  
Genome Scale

scholarly journals SEBINI: Software Environment for BIological Network Inference

2006 ◽  
Vol 22 (21) ◽  
pp. 2706-2708 ◽  
Author(s):  
R. C. Taylor ◽  
A. Shah ◽  
C. Treatman ◽  
M. Blevins
Keyword(s):  
Network Inference ◽  
Biological Network ◽  
Software Environment
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