scholarly journals A convex optimization approach for identification of human tissue-specific interactomes

2016 ◽  
Vol 32 (12) ◽  
pp. i243-i252 ◽  
Author(s):  
Shahin Mohammadi ◽  
Ananth Grama
Keyword(s):  
Convex Optimization ◽  
Human Tissue ◽  
Optimization Approach ◽  
Tissue Specific

scholarly journals A convex optimization approach for identification of human tissue-specific interactomes

2016 ◽  
Author(s):  
Shahin Mohammadi ◽  
Ananth Grama
Keyword(s):  
Human Tissue ◽  
Drug Targets ◽  
Protein Complexes ◽  
Disease Genes ◽  
Optimization Approach ◽  
Cell Type Specificity ◽  
Tissue Specific ◽  
Parkinson’S Diseases ◽  
Coordinated Expression ◽  
Validation Tests

AbstractMotivation:Analysis of organism-specific interactomes has yielded novel insights into cellular function and coordination, understanding of pathology, and identification of markers and drug targets. Genes, however, can exhibit varying levels of cell-type specificity in their expression, and their coordinated expression manifests in tissue-specific function and pathology. Tissue-specific/ selective interaction mechanisms have significant applications in drug discovery, as they are more likely to reveal drug targets. Furthermore, tissue-specific transcription factors (tsTFs) are significantly implicated in human disease, including cancers. Finally, disease genes and protein complexes have the tendency to be differentially expressed in tissues in which defects cause pathology. These observations motivate the construction of refined tissue-specific interactomes from organism-specific interactomes.Results:We present a novel technique for constructing human tissue-specific interactomes. Using a variety of validation tests (ESEA, GO Enrichment, Disease-Gene Subnetwork Compactness), we show that our proposed approach significantly outperforms state of the art techniques. Finally, using case studies of Alzheimer’s and Parkinson’s diseases, we show that tissue-specific interactomes derived from our study can be used to construct pathways implicated in pathology and demonstrate the use of these pathways in identifying novel targets.Availability:http://www.cs.purdue.edu/homes/mohammas/projects/ActPro.html

scholarly journals Maximizing protein translation rate in the non-homogeneous ribosome flow model: a convex optimization approach

2014 ◽  
Vol 11 (100) ◽  
pp. 20140713 ◽  
Author(s):  
Gilad Poker ◽  
Yoram Zarai ◽  
Michael Margaliot ◽  
Tamir Tuller
Keyword(s):  
Synthetic Biology ◽  
Convex Optimization ◽  
Production Rate ◽  
Protein Production ◽  
Flow Model ◽  
Protein Translation ◽  
Optimization Approach ◽  
Initiation Rate ◽  
Translation Rate ◽  
Protein Production Rate

Translation is an important stage in gene expression. During this stage, macro-molecules called ribosomes travel along the mRNA strand linking amino acids together in a specific order to create a functioning protein. An important question, related to many biomedical disciplines, is how to maximize protein production. Indeed, translation is known to be one of the most energy-consuming processes in the cell, and it is natural to assume that evolution shaped this process so that it maximizes the protein production rate. If this is indeed so then one can estimate various parameters of the translation machinery by solving an appropriate mathematical optimization problem. The same problem also arises in the context of synthetic biology, namely, re-engineer heterologous genes in order to maximize their translation rate in a host organism. We consider the problem of maximizing the protein production rate using a computational model for translation–elongation called the ribosome flow model (RFM). This model describes the flow of the ribosomes along an mRNA chain of length n using a set of n first-order nonlinear ordinary differential equations. It also includes n + 1 positive parameters: the ribosomal initiation rate into the mRNA chain, and n elongation rates along the chain sites. We show that the steady-state translation rate in the RFM is a strictly concave function of its parameters. This means that the problem of maximizing the translation rate under a suitable constraint always admits a unique solution, and that this solution can be determined using highly efficient algorithms for solving convex optimization problems even for large values of n . Furthermore, our analysis shows that the optimal translation rate can be computed based only on the optimal initiation rate and the elongation rate of the codons near the beginning of the ORF. We discuss some applications of the theoretical results to synthetic biology, molecular evolution, and functional genomics.

scholarly journals Understanding multicellular function and disease with human tissue-specific networks

2015 ◽  
Vol 47 (6) ◽  
pp. 569-576 ◽  
Author(s):  
Casey S Greene ◽  
Arjun Krishnan ◽  
Aaron K Wong ◽  
Emanuela Ricciotti ◽  
Rene A Zelaya ◽  
...  
Keyword(s):  
Human Tissue ◽  
Tissue Specific
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