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A linear programming model based on network flow for pathway inference
2010
Journal of Systems Science and Complexity
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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
2010
BMC Systems Biology
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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
2013
Molecular Biosystems
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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
2017
BioMed Research International
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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]
2019
bioRxiv
pre-print
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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
2013
PLoS ONE
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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
2011
Physical Biology
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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
2004
Trends in Biotechnology
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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
2004
Bioinformatics
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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
2021
Chemical Society Reviews
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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
2016
Current Opinion in Biotechnology
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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
2013
Frontiers in Genetics
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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
2014
PLoS ONE
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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
2006
PLoS Computational Biology
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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
2005
PLoS Computational Biology
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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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