Inferring protein-protein interaction and protein-DNA interaction directions based on cause-effect pairs in undirected and mixed networks

We consider the following problem: Given an undirected (mixed) network and a set of ordered source-target, or cause-effect pairs, direct all edges so as to maximize the number of pairs that admit a directed source-target path. This is called maximum graph orientation problem, and has applications in...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:arXiv.org 2017-06
Hauptverfasser: Roayaei, Mehdy, Razzazi, MohammadReza
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page
container_title arXiv.org
container_volume
creator Roayaei, Mehdy
Razzazi, MohammadReza
description We consider the following problem: Given an undirected (mixed) network and a set of ordered source-target, or cause-effect pairs, direct all edges so as to maximize the number of pairs that admit a directed source-target path. This is called maximum graph orientation problem, and has applications in understanding interactions in protein-protein interaction networks and protein-DNA interaction networks. We have studied the problem on both undirected and mixed networks. In the undirected case, we determine the parameterized complexity of the problem (for non-fixed and fixed paths) with respect to the number of satisfied pairs, which has been an open problem. Also, we present an exact algorithm which outperforms the previous algorithms on trees with bounded number of leaves. In addition, we present a parameterized-approximation algorithm with respect to a parameter named the number of backbones of a tree. In the mixed case, we present polynomial-time algorithms for the problem on paths and cycles, and an FPT-algorithm based on the combined parameter the number of arcs and the number of pairs on general graphs.
format Article
fullrecord <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_2075659592</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2075659592</sourcerecordid><originalsourceid>FETCH-proquest_journals_20756595923</originalsourceid><addsrcrecordid>eNqNjssKwjAQRYMgWLT_EHBdqKlp7VJ8oBtX7iW2U0nVac2k6C_416ZaBHeu7mXOmWF6zBNRNAlmUyEGzCcqwzAUcSKkjDz23GIBxmg88dpUFjQGXXKNFozKrK6QK8y_fLmb_7BcG3g34kdFkHM3y1RDEEBROMJrpQ25Fd7gx3VOe_CqH64h2HtlzjRi_UJdCPwuh2y8Xu0Xm_afWwNkD2XVGHToIMJExjKVqYj-s14KAlU4</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2075659592</pqid></control><display><type>article</type><title>Inferring protein-protein interaction and protein-DNA interaction directions based on cause-effect pairs in undirected and mixed networks</title><source>Free E- Journals</source><creator>Roayaei, Mehdy ; Razzazi, MohammadReza</creator><creatorcontrib>Roayaei, Mehdy ; Razzazi, MohammadReza</creatorcontrib><description>We consider the following problem: Given an undirected (mixed) network and a set of ordered source-target, or cause-effect pairs, direct all edges so as to maximize the number of pairs that admit a directed source-target path. This is called maximum graph orientation problem, and has applications in understanding interactions in protein-protein interaction networks and protein-DNA interaction networks. We have studied the problem on both undirected and mixed networks. In the undirected case, we determine the parameterized complexity of the problem (for non-fixed and fixed paths) with respect to the number of satisfied pairs, which has been an open problem. Also, we present an exact algorithm which outperforms the previous algorithms on trees with bounded number of leaves. In addition, we present a parameterized-approximation algorithm with respect to a parameter named the number of backbones of a tree. In the mixed case, we present polynomial-time algorithms for the problem on paths and cycles, and an FPT-algorithm based on the combined parameter the number of arcs and the number of pairs on general graphs.</description><identifier>EISSN: 2331-8422</identifier><language>eng</language><publisher>Ithaca: Cornell University Library, arXiv.org</publisher><subject>Algorithms ; Deoxyribonucleic acid ; DNA ; Leaves ; Networks ; Parameterization ; Parameters ; Polynomials ; Proteins</subject><ispartof>arXiv.org, 2017-06</ispartof><rights>2017. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>776,780</link.rule.ids></links><search><creatorcontrib>Roayaei, Mehdy</creatorcontrib><creatorcontrib>Razzazi, MohammadReza</creatorcontrib><title>Inferring protein-protein interaction and protein-DNA interaction directions based on cause-effect pairs in undirected and mixed networks</title><title>arXiv.org</title><description>We consider the following problem: Given an undirected (mixed) network and a set of ordered source-target, or cause-effect pairs, direct all edges so as to maximize the number of pairs that admit a directed source-target path. This is called maximum graph orientation problem, and has applications in understanding interactions in protein-protein interaction networks and protein-DNA interaction networks. We have studied the problem on both undirected and mixed networks. In the undirected case, we determine the parameterized complexity of the problem (for non-fixed and fixed paths) with respect to the number of satisfied pairs, which has been an open problem. Also, we present an exact algorithm which outperforms the previous algorithms on trees with bounded number of leaves. In addition, we present a parameterized-approximation algorithm with respect to a parameter named the number of backbones of a tree. In the mixed case, we present polynomial-time algorithms for the problem on paths and cycles, and an FPT-algorithm based on the combined parameter the number of arcs and the number of pairs on general graphs.</description><subject>Algorithms</subject><subject>Deoxyribonucleic acid</subject><subject>DNA</subject><subject>Leaves</subject><subject>Networks</subject><subject>Parameterization</subject><subject>Parameters</subject><subject>Polynomials</subject><subject>Proteins</subject><issn>2331-8422</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNqNjssKwjAQRYMgWLT_EHBdqKlp7VJ8oBtX7iW2U0nVac2k6C_416ZaBHeu7mXOmWF6zBNRNAlmUyEGzCcqwzAUcSKkjDz23GIBxmg88dpUFjQGXXKNFozKrK6QK8y_fLmb_7BcG3g34kdFkHM3y1RDEEBROMJrpQ25Fd7gx3VOe_CqH64h2HtlzjRi_UJdCPwuh2y8Xu0Xm_afWwNkD2XVGHToIMJExjKVqYj-s14KAlU4</recordid><startdate>20170603</startdate><enddate>20170603</enddate><creator>Roayaei, Mehdy</creator><creator>Razzazi, MohammadReza</creator><general>Cornell University Library, arXiv.org</general><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20170603</creationdate><title>Inferring protein-protein interaction and protein-DNA interaction directions based on cause-effect pairs in undirected and mixed networks</title><author>Roayaei, Mehdy ; Razzazi, MohammadReza</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-proquest_journals_20756595923</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Algorithms</topic><topic>Deoxyribonucleic acid</topic><topic>DNA</topic><topic>Leaves</topic><topic>Networks</topic><topic>Parameterization</topic><topic>Parameters</topic><topic>Polynomials</topic><topic>Proteins</topic><toplevel>online_resources</toplevel><creatorcontrib>Roayaei, Mehdy</creatorcontrib><creatorcontrib>Razzazi, MohammadReza</creatorcontrib><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Roayaei, Mehdy</au><au>Razzazi, MohammadReza</au><format>book</format><genre>document</genre><ristype>GEN</ristype><atitle>Inferring protein-protein interaction and protein-DNA interaction directions based on cause-effect pairs in undirected and mixed networks</atitle><jtitle>arXiv.org</jtitle><date>2017-06-03</date><risdate>2017</risdate><eissn>2331-8422</eissn><abstract>We consider the following problem: Given an undirected (mixed) network and a set of ordered source-target, or cause-effect pairs, direct all edges so as to maximize the number of pairs that admit a directed source-target path. This is called maximum graph orientation problem, and has applications in understanding interactions in protein-protein interaction networks and protein-DNA interaction networks. We have studied the problem on both undirected and mixed networks. In the undirected case, we determine the parameterized complexity of the problem (for non-fixed and fixed paths) with respect to the number of satisfied pairs, which has been an open problem. Also, we present an exact algorithm which outperforms the previous algorithms on trees with bounded number of leaves. In addition, we present a parameterized-approximation algorithm with respect to a parameter named the number of backbones of a tree. In the mixed case, we present polynomial-time algorithms for the problem on paths and cycles, and an FPT-algorithm based on the combined parameter the number of arcs and the number of pairs on general graphs.</abstract><cop>Ithaca</cop><pub>Cornell University Library, arXiv.org</pub><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier EISSN: 2331-8422
ispartof arXiv.org, 2017-06
issn 2331-8422
language eng
recordid cdi_proquest_journals_2075659592
source Free E- Journals
subjects Algorithms
Deoxyribonucleic acid
DNA
Leaves
Networks
Parameterization
Parameters
Polynomials
Proteins
title Inferring protein-protein interaction and protein-DNA interaction directions based on cause-effect pairs in undirected and mixed networks
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-22T21%3A10%3A24IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=document&rft.atitle=Inferring%20protein-protein%20interaction%20and%20protein-DNA%20interaction%20directions%20based%20on%20cause-effect%20pairs%20in%20undirected%20and%20mixed%20networks&rft.jtitle=arXiv.org&rft.au=Roayaei,%20Mehdy&rft.date=2017-06-03&rft.eissn=2331-8422&rft_id=info:doi/&rft_dat=%3Cproquest%3E2075659592%3C/proquest%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2075659592&rft_id=info:pmid/&rfr_iscdi=true