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Designing pooling systems for noisy high-throughput protein-protein interaction experiments using boolean compressed sensing

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dc.contributor.author Mourad R.
dc.contributor.author Dawy Z.
dc.contributor.author Morcos F.
dc.contributor.editor
dc.date 2013
dc.date.accessioned 2017-09-07T07:08:17Z
dc.date.available 2017-09-07T07:08:17Z
dc.date.issued 2013
dc.identifier 10.1109/TCBB.2013.129
dc.identifier.isbn
dc.identifier.issn 15455963
dc.identifier.uri http://hdl.handle.net/10938/11847
dc.description.abstract Group testing, also known as pooling, is a common technique used in high-throughput experiments in molecular biology to significantly reduce the number of tests required to identify rare biological interactions while correcting for experimental noise. Central to the group testing problem are 1) a pooling design that lays out how items are grouped together into pools for testing and 2) a decoder that interprets the results of the tested pools, identifying the active compounds. In this work, we take advantage of decoder guarantees from the field of compressed sensing (CS) to address the problem of efficient and reliable detection of biological interaction in noisy high-throughput experiments. We also use efficient combinatorial algorithms from group testing as well as established measurement matrices from CS to create pooling designs. First, we formulate the group testing problem in terms of a Boolean CS framework. We then propose a low-complexity l1-norm decoder to interpret pooling test results and identify active compounds. We demonstrate the robustness of the proposed l1-norm decoder in simulated experiments with false-positive and false-negative error rates typical of high-throughput experiments. When benchmarked against the current state-of-the-art methods, the proposed l1-norm decoder provides superior error correction for the majority of the cases considered while being notably faster computationally. Additionally, we test the performance of the l1-norm decoder against a real experimental data set, where 12,675 prey proteins were screened against 12 bait proteins. Lastly, we study the impact of different sparse pooling design matrices on decoder performance and show that the shifted transversal design (STD) is the most suitable among the pooling designs surveyed for biological applications of CS. © 2013 IEEE.
dc.format.extent
dc.format.extent Pages: (1478-1490)
dc.language English
dc.publisher LOS ALAMITOS
dc.relation.ispartof Publication Name: IEEE-ACM Transactions on Computational Biology and Bioinformatics; Publication Year: 2013; Volume: 10; no. 6; Pages: (1478-1490);
dc.relation.ispartofseries
dc.relation.uri
dc.source Scopus
dc.subject.other
dc.title Designing pooling systems for noisy high-throughput protein-protein interaction experiments using boolean compressed sensing
dc.type Article
dc.contributor.affiliation Mourad, R., Department of Electrical and Computer Engineering, American University of Beirut, Riad El Solh, Beirut 1107 2020, Lebanon
dc.contributor.affiliation Dawy, Z., Department of Electrical and Computer Engineering, American University of Beirut, Riad El Solh, Beirut 1107 2020, Lebanon
dc.contributor.affiliation Morcos, F., Center for Theoretical Biological Physics at Rice University, Houston, TX 77005, United States
dc.contributor.authorAddress Department of Electrical and Computer Engineering, American University of Beirut, Riad El Solh, Beirut 1107 2020, Lebanon
dc.contributor.authorCorporate University: American University of Beirut; Faculty: Faculty of Engineering and Architecture; Department: Electrical and Computer Engineering;
dc.contributor.authorDepartment Electrical and Computer Engineering
dc.contributor.authorDivision
dc.contributor.authorEmail ram51@aub.edu.lb; zaher.dawy@aub.edu.lb; faruckm@rice.edu
dc.contributor.authorFaculty Faculty of Engineering and Architecture
dc.contributor.authorInitials Mourad, R
dc.contributor.authorInitials Dawy, Z
dc.contributor.authorInitials Morcos, F
dc.contributor.authorOrcidID
dc.contributor.authorReprintAddress Mourad, R (reprint author), Amer Univ Beirut, Dept Elect and Comp Engn, Beirut 11072020, Lebanon.
dc.contributor.authorResearcherID
dc.contributor.authorUniversity American University of Beirut
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dc.format.extentCount 13
dc.identifier.articleNo 6646169
dc.identifier.coden
dc.identifier.pubmedID 24407306
dc.identifier.scopusID 84894532626
dc.identifier.url
dc.publisher.address 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1314 USA
dc.relation.ispartofConference
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dc.relation.ispartofConferenceDate
dc.relation.ispartofConferenceHosting
dc.relation.ispartofConferenceLoc
dc.relation.ispartofConferenceSponsor
dc.relation.ispartofConferenceTitle
dc.relation.ispartofFundingAgency
dc.relation.ispartOfISOAbbr IEEE-ACM Trans. Comput. Biol. Bioinform.
dc.relation.ispartOfIssue 6
dc.relation.ispartOfPart
dc.relation.ispartofPubTitle IEEE-ACM Transactions on Computational Biology and Bioinformatics
dc.relation.ispartofPubTitleAbbr IEEE-ACM Trans. Comput. BioL. Bioinf.
dc.relation.ispartOfSpecialIssue
dc.relation.ispartOfSuppl
dc.relation.ispartOfVolume 10
dc.source.ID WOS:000332481000014
dc.type.publication Journal
dc.subject.otherAuthKeyword Boolean compressed sensing
dc.subject.otherAuthKeyword Group testing
dc.subject.otherAuthKeyword Protein-protein interactions
dc.subject.otherAuthKeyword Shifted transversal pooling design (STD)
dc.subject.otherAuthKeyword Yeast two-hybrid (Y2H) experiments
dc.subject.otherChemCAS
dc.subject.otherIndex algorithm
dc.subject.otherIndex article
dc.subject.otherIndex biology
dc.subject.otherIndex computer language
dc.subject.otherIndex computer program
dc.subject.otherIndex computer simulation
dc.subject.otherIndex information processing
dc.subject.otherIndex laboratory diagnosis
dc.subject.otherIndex methodology
dc.subject.otherIndex protein analysis
dc.subject.otherIndex reproducibility
dc.subject.otherIndex signal processing
dc.subject.otherIndex theoretical model
dc.subject.otherIndex two hybrid system
dc.subject.otherIndex Algorithms
dc.subject.otherIndex Computational Biology
dc.subject.otherIndex Computer Simulation
dc.subject.otherIndex Data Compression
dc.subject.otherIndex False Negative Reactions
dc.subject.otherIndex Models, Theoretical
dc.subject.otherIndex Programming Languages
dc.subject.otherIndex Protein Interaction Mapping
dc.subject.otherIndex Reproducibility of Results
dc.subject.otherIndex Signal Processing, Computer-Assisted
dc.subject.otherIndex Software
dc.subject.otherIndex Two-Hybrid System Techniques
dc.subject.otherKeywordPlus SHIFTED TRANSVERSAL DESIGN
dc.subject.otherKeywordPlus SPARSE MATRICES
dc.subject.otherKeywordPlus 2-HYBRID SYSTEM
dc.subject.otherKeywordPlus NETWORK
dc.subject.otherKeywordPlus RECOVERY
dc.subject.otherKeywordPlus SMART
dc.subject.otherKeywordPlus RECONSTRUCTION
dc.subject.otherKeywordPlus IDENTIFICATION
dc.subject.otherKeywordPlus STRATEGY
dc.subject.otherWOS Biochemical Research Methods
dc.subject.otherWOS Computer Science, Interdisciplinary Applications
dc.subject.otherWOS Mathematics, Interdisciplinary Applications
dc.subject.otherWOS Statistics and Probability


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