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A linear programming model based on network flow for pathway inference

Xianwen Ren, Xiang-Sun Zhang
2010 Journal of Systems Science and Complexity  
This paper proposes a novel approach to infer the pathways based on the network flow well studied in the operation research.  ...  The approach is formulated to a linear programming model and solved by the simplex method.  ...  Based on the edge-weighted network, the pathway-inference problem is transformed into a maximum-flow problem.  ... 
doi:10.1007/s11424-010-0206-z fatcat:46iwz3eejfdoreovca4744hhja

An information-flow-based model with dissipation, saturation and direction for active pathway inference

Xianwen Ren, Xiaobo Zhou, Ling-Yun Wu, Xiang-Sun Zhang
2010 BMC Systems Biology  
The model is formulated as a linear programming problem and thus is solved efficiently.  ...  The deduced linear programming should be a promising tool to infer the various biological pathways from the high-throughput data.  ...  The linear programming model should be a promising tool to mine the huge biological network dataset in the future.  ... 
doi:10.1186/1752-0509-4-72 pmid:20504374 pmcid:PMC2890502 fatcat:7ncqy3lsb5gu7lvotjxfknmtge

iPoint: an integer programming based algorithm for inferring protein subnetworks

Nir Atias, Roded Sharan
2013 Molecular Biosystems  
Here we devise an integer linear programming formulation for the joint optimization problem, allowing us to solve it to optimality in minutes on current networks.  ...  The interpretation of such data, particularly in the context of a protein interaction network, has the potential to shed light on the molecular pathways underlying the phenotype or the process in question  ...  Acknowledgements We thank Nir Yosef for his help and fruitful discussions regarding this work. NA was supported in part by a fellowship from the Edmond J.  ... 
doi:10.1039/c3mb25432a pmid:23385645 fatcat:grnly6on3fasnokbbs5g2v72oe

Mathematical and Computational Modeling in Complex Biological Systems

Zhiwei Ji, Ke Yan, Wenyang Li, Haigen Hu, Xiaoliang Zhu
2017 BioMed Research International  
Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases.  ...  The biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors.  ...  Simplistically, linear programming is the optimization of an outcome based on some set of constraints using a linear mathematical model.  ... 
doi:10.1155/2017/5958321 pmid:28386558 pmcid:PMC5366773 fatcat:e6pyjhqdyzfllk6q2l5yjzssf4

GIP: A Gene network-based integrative approach for Inferring disease-associated signaling Pathways [article]

Xi Chen
2019 bioRxiv   pre-print
We develop a Gene network-based integrative approach for Inferring disease-associated signaling Pathways (GIP). Specifically, we identify alternative pathways given source and target proteins.  ...  associated with a disease.  ...  To reconstruct aberrant pathway modules in cancer studies, we develop a Gene network-based integrative approach for Inferring disease-associated signaling Pathways (GIP).  ... 
doi:10.1101/654780 fatcat:gjjrpep4vrbntgx2syval2goqq

Reconstruction of Cellular Signal Transduction Networks Using Perturbation Assays and Linear Programming

Bettina Knapp, Lars Kaderali, Hans A. Kestler
2013 PLoS ONE  
We formulate network inference as a linear optimization problem, which can be solved efficiently even for large-scale systems.  ...  One of the problems in network inference is the exponential number of possible network topologies for a given number of genes.  ...  We would furthermore like to thank Holger Fröhlich for helpful discussion on DEPNs and equivalence classes, as well as three referees for their valuable comments.  ... 
doi:10.1371/journal.pone.0069220 pmid:23935958 pmcid:PMC3728289 fatcat:a3e5jyvhcfbpledkpswjqpmfi4

Modeling information flow in biological networks

Yoo-Ah Kim, Jozef H Przytycki, Stefan Wuchty, Teresa M Przytycka
2011 Physical Biology  
In this paper, we first provide an overview of the state of the art of research in the network analysis based on information flow models.  ...  Motivated by applications to inferring information flow from genotype to phenotype in a very large human interaction network, we generalized previous approaches to compute information flows for a large  ...  model by formulating a linear programming problem.  ... 
doi:10.1088/1478-3975/8/3/035012 pmid:21572171 pmcid:PMC3148109 fatcat:zheja2twrfddxmc2xj5dx3w4n4

The regulatory software of cellular metabolism

D SEGRE
2004 Trends in Biotechnology  
This pattern is suggested to confirm the preference for linear flows along pathways.  ...  A simple kinetic model for a branch point in a metabolic network is presented here to illustrate the connection between enzyme concentrations and fluxes.  ... 
doi:10.1016/j.tibtech.2004.04.013 pmid:15158051 fatcat:2qlbe664era2nowf4v5seiw5qm

GeneNetwork: an interactive tool for reconstruction of genetic networks using microarray data

C.-C. Wu, H.-C. Huang, H.-F. Juan, S.-T. Chen
2004 Bioinformatics  
GeneNetwork enables a user to readily reconstruct genetic networks based on microarray data without having intimate knowledge of the mathematical models.  ...  We have developed an interactive tool, GeneNetwork, which provides four reverse engineering models and three data interpolation approaches to infer relationships between genes.  ...  We gratefully acknowledge the support of the National Research Program for Genomic Medicine of National Science Council, Taiwan (NSC 91-3112-13-001-002 and NSC 92-3112-B-027-001).  ... 
doi:10.1093/bioinformatics/bth428 pmid:15271782 fatcat:fla6k44r2bdvpjwd36vsllhlsm

Chemical data intelligence for sustainable chemistry

Jana M. Weber, Zhen Guo, Chonghuan Zhang, Artur M. Schweidtmann, Alexei A. Lapkin
2021 Chemical Society Reviews  
This study highlights new opportunities for optimal reaction route selection from large chemical databases brought about by the rapid digitalisation of chemical data.  ...  Linear programming Linear programming (LP) problems consist out of a linear objective function and linear constraints.  ...  models mass flows and reactions through linear balance equations for all components.  ... 
doi:10.1039/d1cs00477h pmid:34520507 fatcat:lcvtptg2zvbgnfrkjrysjzsoj4

Network-based approaches for analysis of complex biological systems

Deborah Chasman, Alireza Fotuhi Siahpirani, Sushmita Roy
2016 Current Opinion in Biotechnology  
functions (reviewed by Kim et al. [11]). 30 Expression-based network inference has been approached in two ways: by reconstructing regulatory programs for (i) individual genes at a time ("per-gene" methods  ...  Some recent work combines the two paradigms [13], providing a single method to infer regulatory programs for individual genes and gene 35 modules.  ...  Aiming to get closer to a directed regulatory network, Ontogenet [54]* infers per-module regulatory programs for 100 multiple cell types in a lineage.  ... 
doi:10.1016/j.copbio.2016.04.007 pmid:27115495 fatcat:3ppskhtoifbobayer5bzpqz6qq

Bridging the Gap between Genotype and Phenotype via Network Approaches

Yoo-Ah Kim, Teresa M. Przytycka
2013 Frontiers in Genetics  
To address this emerging need, computational approaches increasingly utilize a pathway-centric perspective.  ...  In this review, we survey recently developed network based methods that attempt to bridge the genotype-phenotype gap.  ...  We review here two different types of network flow approaches that can model such system -current flow network and minimum cost network flow.  ... 
doi:10.3389/fgene.2012.00227 pmid:23755063 pmcid:PMC3668153 fatcat:hbj7ddx5sjf3hha5gluhywha2a

Integrating Genomics and Proteomics Data to Predict Drug Effects Using Binary Linear Programming

Zhiwei Ji, Jing Su, Chenglin Liu, Hongyan Wang, Deshuang Huang, Xiaobo Zhou, Hans A. Kestler
2014 PLoS ONE  
Binary linear programming (BLP) was then developed to optimize the generic pathway topology based on the mid-stage signaling response of phosphorylation.  ...  The first group of 11 compounds was utilized to optimize the generic pathways, and then 4 compounds were used to identify effects based on the inferred cell-specific pathways.  ...  Hongwei Shao, Xiaoqiang Sun, and Qianqian Song at the Center for Bioinformatics and Systems Biology at Wake Forest School of Medicine. Author Contributions  ... 
doi:10.1371/journal.pone.0102798 pmid:25036040 pmcid:PMC4103865 fatcat:cezrwhonpfftzkzg2x3mfjarkq

Computational Inference of Neural Information Flow Networks

V. Anne Smith, Jing Yu, Tom V. Smulders, Alexander J. Hartemink, Erich D. Jarvis
2006 PLoS Computational Biology  
Determining how information flows along anatomical brain pathways is a fundamental requirement for understanding how animals perceive their environments, learn, and behave.  ...  A linear method applied to the same data incorrectly produces networks with information flow to non-neural tissue and over paths known not to exist.  ...  JY developed the Cþþ network inference algorithm based on code from AJH. VAS, AJH, and EDJ wrote the paper. Funding.  ... 
doi:10.1371/journal.pcbi.0020161 pmid:17121460 pmcid:PMC1664702 fatcat:pudwll7sx5dk3jr5khrblgehxu

Computational Inference of Neural Information Flow Networks

V Anne Smith, Jing Yu, Tom Smulders, Alexander J. Hartemink, Erich David Jarvis
2005 PLoS Computational Biology  
Determining how information flows along anatomical brain pathways is a fundamental requirement for understanding how animals perceive their environments, learn, and behave.  ...  A linear method applied to the same data incorrectly produces networks with information flow to non-neural tissue and over paths known not to exist.  ...  JY developed the Cþþ network inference algorithm based on code from AJH. VAS, AJH, and EDJ wrote the paper. Funding.  ... 
doi:10.1371/journal.pcbi.0020161.eor fatcat:2ydvpcybizdxdctdtuji6efuv4
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