Diego Galeano, Shantao Li, Mark Gerstein & Alberto Paccanaro
Predicting the frequencies of drug side effects
Nature Communications; DOI: https://doi.org/10.1038/s41467-020-18305-y (2020).
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Cheng Ye, Alberto Paccanaro, Mark Gerstein & Koon-Kiu Yan
The corrected gene proximity map for analyzing the 3D genome organization using Hi-C data
BMC Bioinformatics; DOI: https://doi.org/10.1186/s12859-020-03545-y (2020).
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Jessica Gliozzo, Paolo Perlasca, Marco Mesiti, Elena Casiraghi, Viviana Vallacchi, Elisabetta Vergani, Marco Frasca, Giuliano Grossi, Alessandro Petrini, Matteo Re, Alberto Paccanaro & Giorgio Valentini
Network modeling of patients’ biomolecular profiles for clinical phenotype/outcome prediction
Scientific Reports; DOI: https://doi.org/10.1038/s41598-020-60235-8 (2020).
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Joanna C. Dawes, Philip Webster, Barbara Iadarola, Claudia Garcia-Diaz, Marian Dore, Bruce J. Bolt, Hamlata Dewchand, Gopuraja Dharmalingam, Alex P. McLatchie, Jakub Kaczor, Juan J. Caceres, Alberto Paccanaro, Laurence Game, Simona Parrinello & Anthony G. Uren
LUMI-PCR: an Illumina platform ligation-mediated PCR protocol for integration site cloning, provides molecular quantitation of integration sites
BMC Mobile DNA; DOI: https://doi.org/10.1186/s13100-020-0201-4 (2020).
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Naihui Zhou, Yuxiang Jiang, Timothy R. Bergquist, Alexandra J. Lee, Balint Z. Kacsoh, Alex W. Crocker, Kimberley A. Lewis, George Georghiou, Huy N. Nguyen, Md Nafiz Hamid, Larry Davis, Tunca Dogan, Volkan Atalay, Ahmet S. Rifaioglu, Alperen Dalkıran, Rengul Cetin Atalay, Chengxin Zhang, Rebecca L. Hurto, Peter L. Freddolino, Yang Zhang, Prajwal Bhat, Fran Supek, José M. Fernández, Branislava Gemovic, Vladimir R. Perovic, Radoslav S. Davidović, Neven Sumonja, Nevena Veljkovic, Ehsaneddin Asgari, Mohammad R.K. Mofrad, Giuseppe Profiti, Castrense Savojardo, Pier Luigi Martelli, Rita Casadio, Florian Boecker, Heiko Schoof, Indika Kahanda, Natalie Thurlby, Alice C. McHardy, Alexandre Renaux, Rabie Saidi, Julian Gough, Alex A. Freitas, Magdalena Antczak, Fabio Fabris, Mark N. Wass, Jie Hou, Jianlin Cheng, Zheng Wang, Alfonso E. Romero, Alberto Paccanaro, Haixuan Yang, Tatyana Goldberg, Chenguang Zhao, Liisa Holm, Petri Törönen, Alan J. Medlar, Elaine Zosa, Itamar Borukhov, Ilya Novikov, Angela Wilkins, Olivier Lichtarge, Po-Han Chi, Wei-Cheng Tseng, Michal Linial, Peter W. Rose, Christophe Dessimoz, Vedrana Vidulin, Saso Dzeroski, Ian Sillitoe, Sayoni Das, Jonathan Gill Lees, David T. Jones, Cen Wan, Domenico Cozzetto, Rui Fa, Mateo Torres, Alex Warwick Vesztrocy, Jose Manuel Rodriguez, Michael L. Tress, Marco Frasca, Marco Notaro, Giuliano Grossi, Alessandro Petrini, Matteo Re, Giorgio Valentini, Marco Mesiti, Daniel B. Roche, Jonas Reeb, David W. Ritchie, Sabeur Aridhi, Seyed Ziaeddin Alborzi, Marie-Dominique Devignes, Da Chen Emily Koo, Richard Bonneau, Vladimir Gligorijević, Meet Barot, Hai Fang, Stefano Toppo, Enrico Lavezzo, Marco Falda, Michele Berselli, Silvio C.E. Tosatto, Marco Carraro, Damiano Piovesan, Hafeez Ur Rehman, Qizhong Mao, Shanshan Zhang, Slobodan Vucetic, Gage S. Black, Dane Jo, Erica Suh, Jonathan B. Dayton, Dallas J. Larsen, Ashton R. Omdahl, Liam J. McGuffin, Danielle A. Brackenridge, Patricia C. Babbitt, Jeffrey M. Yunes, Paolo Fontana, Feng Zhang, Shanfeng Zhu, Ronghui You, Zihan Zhang, Suyang Dai, Shuwei Yao, Weidong Tian, Renzhi Cao, Caleb Chandler, Miguel Amezola, Devon Johnson, Jia-Ming Chang, Wen-Hung Liao, Yi-Wei Liu, Stefano Pascarelli, Yotam Frank, Robert Hoehndorf, Maxat Kulmanov, Imane Boudellioua, Gianfranco Politano, Stefano Di Carlo, Alfredo Benso, Kai Hakala, Filip Ginter, Farrokh Mehryary, Suwisa Kaewphan, Jari Björne, Hans Moen, Martti E.E. Tolvanen, Tapio Salakoski, Daisuke Kihara, Aashish Jain, Tomislav Šmuc, Adrian Altenhoff, Asa Ben-Hur, Burkhard Rost, Steven E. Brenner, Christine A. Orengo, Constance J. Jeffery, Giovanni Bosco, Deborah A. Hogan, Maria J. Martin, Claire O’Donovan, Sean D. Mooney, Casey S. Greene, Predrag Radivojac & Iddo Friedberg
The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens.
Genome Biology; DOI: https://doi.org/10.1186/s13059-019-1835-8 (2019).
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Juan J. Cáceres, Alberto Paccanaro
Disease gene prediction for molecularly uncharacterized diseases
PLOS Computational Biology; DOI: https://doi.org/10.1371/journal.pcbi.1007078 (2019).
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Fabrizio Frasca, Diego Galeano, Guadalupe Gonzalez, Ivan Laponogov, Kirill Veselkov, Alberto Paccanaro, and Michael M. Bronstein
Learning interpretable disease self-representations for drug repositioning
arXiv:1909.06609 — NeurIPS Graph Representation Learning Workshop; (2019).
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Diego Galeano & Alberto Paccanaro
Predicting the frequencies of drug side effects
bioRxiv (2019): 594465; DOI: https://doi.org/10.1101/594465 (2019).
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Diego Galeano & Alberto Paccanaro
The Geometric Sparse Matrix Completion Model for Predicting Drug Side effects
bioRxiv (2019): 652412; DOI: https://doi.org/10.1101/652412 (2019).
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Philip Webster, Joanna Dawes, Hamlata Dewchand, Katalin Takacs, Barbara Iadarola, Bruce Bolt, Juan Caceres, Jakub Kaczor, Gopuraja Dharmalingam, Marian Dore, Laurence Game, Thomas Adejumo, James Elliott, Kikkeri Naresh, Mohammad Mahdi Karimi, Katerina Rekopoulou, Ge Tan, Alberto Paccanaro, and Anthony Uren
Subclonal mutation selection in mouse lymphomagenesis identifies known cancer loci and suggests novel candidates
Nature Communications; DOI: 10.1038/s41467-018-05069-9
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Diego Galeano & Alberto Paccanaro
A recommender system approach for predicting drug side effects
International Joint Conference on Neural Networks (IJCNN), pp. 1-8. IEEE; DOI: 10.1109/IJCNN.2018.8489025 (2018).
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Fabio Manfredini, Alfonso E Romero, Inti Pedroso Alberto Paccanaro, Seirian Sumner and Mark J F Brown
Neurogenomic Signatures of Successes and Failures in Life-History Transitions in a Key Insect Pollinator
Genome Biology and Evolution; DOI: 10.1093/gbe/evx220 (2017).
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Horacio Caniza, Diego Galeano & Alberto Paccanaro
Mining the biomedical literature to predict shared drug targets in DrugBank
XLIII Latin American Computer Conference (CLEI), pp. 1-5. IEEE; DOI: 10.1109/CLEI.2017.8226376 (2017).
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Yuxiang Jiang, Tal Ronnen Oron, Wyatt T. Clark, Asma R. Bankapur, Daniel D’Andrea, Rosalba Lepore, Christopher S. Funk, Indika Kahanda, Karin M. Verspoor, Asa Ben-Hur, Da Chen Emily Koo, Duncan Penfold-Brown, Dennis Shasha, Noah Youngs, Richard Bonneau, Alexandra Lin, Sayed M. E. Sahraeian, Pier Luigi Martelli, Giuseppe Profiti, Rita Casadio, Renzhi Cao, Zhaolong Zhong, Jianlin Cheng, Adrian Altenhoff, Nives Skunca, Christophe Dessimoz, Tunca Dogan, Kai Hakala, Suwisa Kaewphan, Farrokh Mehryary, Tapio Salakoski, Filip Ginter, Hai Fang, Ben Smithers, Matt Oates, Julian Gough, Petri Törönen, Patrik Koskinen, Liisa Holm, Ching-Tai Chen, Wen-Lian Hsu, Kevin Bryson, Domenico Cozzetto, Federico Minneci, David T. Jones, Samuel Chapman, Dukka BKC, Ishita K. Khan, Daisuke Kihara, Dan Ofer, Nadav Rappoport, Amos Stern, Elena Cibrian-Uhalte, Paul Denny, Rebecca E. Foulger, Reija Hieta, Duncan Legge, Ruth C. Lovering, Michele Magrane, Anna N. Melidoni, Prudence Mutowo-Meullenet, Klemens Pichler, Aleksandra Shypitsyna, Biao Li, Pooya Zakeri, Sarah ElShal, Léon-Charles Tranchevent, Sayoni Das, Natalie L. Dawson, David Lee, Jonathan G. Lees, Ian Sillitoe, Prajwal Bhat, Tamás Nepusz, Alfonso E. Romero, Rajkumar Sasidharan, Haixuan Yang, Alberto Paccanaro, … Iddo Friedberg and Predrag Radivojac
An expanded evaluation of protein function prediction methods shows an improvement in accuracy
Genome Biology; DOI: 10.1186/s13059-016-1037-6 (2016).
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Michael J. Meyer, Ryan Lapcevic, Alfonso E. Romero, Mark Yoon, Jishnu Das, Juan Felipe Beltran, Matthew Mort, Peter D. Stenson, David N. Cooper, Alberto Paccanaro,and Haiyuan Yu
mutation3D: Cancer Gene Prediction Through Atomic Clustering of Coding Variants in the Structural Proteome
Human Mutation; DOI: 10.1002/humu.22963 (2016).
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Diego Galeano & Alberto Paccanaro
Drug targets prediction using chemical similarity
XLII Latin American Computing Conference (CLEI), pp. 1-7. IEEE; DOI: 10.1109/CLEI.2016.7833353 (2016).
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H. Caniza, A. E. Romero and A. Paccanaro,
A network medicine approach to quantify distance between hereditary disease modules on the interactome
Nature Scientific Reports 5, 17658; doi: 10.1038/srep17658 (2015).
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H. Caniza, A. E. Romero, S. Heron, H. Yang, A. Devoto, M. Frasca, M. Mesiti, G. Valentini, and A. Paccanaro,
GOssTo: a user-friendly stand-alone and web tool for calculating semantic similarities on the Gene Ontology
Bioinformatics, vol. 30, iss. pp. 2235-2236, 2014.
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S. P. Smieszek, H. Yang, A. Paccanaro, and P. F. Devlin,
Progressive promoter element combinations classify conserved orthogonal plant circadian gene expression modules
Journal of The Royal Society Interface, vol. 11, iss. 99, 20140535, 2014
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G. Valentini, A. Paccanaro, H. Caniza, A. E. Romero, and M. Re
An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods
Artificial intelligence in medicine, vol. 61, iss. 2, pp. 63-78, 2014.
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T. Nepusz and A. Paccanaro
Structural Pattern Discovery in Protein-Protein Interaction Networks
in I. King, and K. Huang (Eds.) Springer Handbook of Bio-/Neuroinformatics, pp. 375-398, 2014.
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P. Radivojac, W. T. Clark, T. R. Oron, A. M. Schnoes, T. Wittkop, A. Sokolov, K. Graim, C. Funk, K. Verspoor, A. Ben-Hur, G. Pandey, J. M. Yunes, A. S. Talwalkar, S. Repo, M. L. Souza, D. Piovesan, R. Casadio, Z. Wang, J. Cheng, H. Fang, J. Gough, P. Koskinen, P. Toronen, J. Nokso-Koivisto, L. Holm, D. Cozzetto, D. W. A. Buchan, K. Bryson, D. T. Jones, B. Limaye, H. Inamdar, A. Datta, S. K. Manjari, R. Joshi, M. Chitale, D. Kihara, A. M. Lisewski, S. Erdin, E. Venner, O. Lichtarge, R. Rentzsch, H. Yang, A. E. Romero, P. Bhat, A. Paccanaro, T. Hamp, R. Kaszner, S. Seemayer, E. Vicedo, C. Schaefer, D. Achten, F. Auer, A. Boehm, T. Braun, M. Hecht, M. Heron, P. Honigschmid, T. A. Hopf, S. Kaufmann, M. Kiening, D. Krompass, C. Landerer, Y. Mahlich, M. Roos, J. Bjorne, T. Salakoski, A. Wong, H. Shatkay, F. Gatzmann, I. Sommer, M. N. Wass, M. J. E. Sternberg, N. Skunca, F. Supek, M. Bosnjak, P. Panov, S. Dzeroski, T. Smuc, Y. A. I. Kourmpetis, A. D. J. van Dijk, C. J. Braak, Y. Zhou, Q. Gong, X. Dong, W. Tian, M. Falda, P. Fontana, E. Lavezzo, B. Di Camillo, S. Toppo, L. Lan, N. Djuric, Y. Guo, S. Vucetic, A. Bairoch, M. Linial, P. C. Babbitt, S. E. Brenner, C. Orengo, B. Rost, S. D. Mooney, and I. Friedberg
A large-scale evaluation of computational protein function prediction
Nature Methods, 10(3):221-7, 2013.
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P. C. Havugimana, T. G. Hart, T. Nepusz, H. Yang, A. L. Turinsky, Z. Li, P. I. Wang, D. R. Boutz, V. Fong, S. Phanse, M. Babu, S. A. Craig, P. Hu, C. Wan, J. Vlasblom, V. U. Dar, A. Bezginov, G. W. Clark, G. C. Wu, S. J. Wodak, E. R. Tillier, A. Paccanaro, E. M. Marcotte, and A. Emili
A census of human soluble protein complexes
Cell, vol. 150, iss. 5, pp. 1068-1081, 2012.
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H. Yang, T. Nepusz, and A. Paccanaro
Improving GO semantic similarity measures by exploring the ontology beneath the terms and modelling uncertainty
Bioinformatics, vol. 28, iss. 10, pp. 1383-1389, 2012.
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R. Sasidharan, T. Nepusz, D. Swarbreck, E. Huala, and A. Paccanaro
GFam: a platform for automatic annotation of gene families
Nucleic Acids Research, vol. 40, iss. 19, p. 152, 2012.
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T. Nepusz, H. Yu, and A. Paccanaro
Detecting overlapping protein complexes in protein-protein interaction networks
Nature Methods, vol. 9, pp. 471-472, 2012.
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P. Abbruscato, T. Nepusz, L. Mizzi, M. Del Corvo, P. Morandini, I. Fumasoni, C. Michel, A. Paccanaro, E. Guiderdoni, U. Schaffrath, J. Morel, P. Piffanelli, and O. Faivre-Rampant
OsWRKY22, a monocot WRKY gene, plays a role in the resistance response to blast: OsWRKY22 role in rice resistance to blast
Molecular Plant Pathology, vol. 13, iss. 8, pp. 828-841, 2012.
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P. Bhat, H. Yang, L. Bögre, A. Devoto, and A. Paccanaro
Computational Selection of Transcriptomics Experiments Improves Guilt-by-Association Analyses
PLoS ONE, vol. 7, iss. 8, p. 39681, 2012.
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R. Dóczi, L. Ökrész, A. E. Romero, A. Paccanaro, and L. Bögre
Exploring the evolutionary path of plant MAPK networks
Trends in Plant Science, vol. 17, iss. 9, pp. 518-525, 2012.
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T. Nepusz, R. Sasidharan, and A. Paccanaro
SCPS: a fast implementation of a spectral method for detecting protein families on a genome-wide scale
BMC Bioinformatics, vol. 11, iss. 1, p. 120, 2010.
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P. Hu, S. C. Janga, M. Babu, J. J. Díaz-Mejía, G. Butland, W. Yang, O. Pogoutse, X. Guo, S. Phanse, P. Wong, S. Chandran, C. Christopoulos, A. Nazarians-Armavil, N. K. Nasseri, G. Musso, M. Ali, N. Nazemof, V. Eroukova, A. Golshani, A. Paccanaro, J. F. Greenblatt, G. Moreno-Hagelsieb, and A. Emili
Global Functional Atlas of Escherichia coli Encompassing Previously Uncharacterized Proteins
PLoS Biol, vol. 7, iss. 4, p. 1000096, 2009.
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T. A. Gianoulis, J. Raes, P. V. Patel, R. Bjornson, J. O. Korbel, I. Letunic, T. Yamada, A. Paccanaro, L. J. Jensen, M. Snyder, P. Bork, and M. B. Gerstein
Quantifying environmental adaptation of metabolic pathways in metagenomics
Proceedings of the National Academy of Sciences, vol. 106, iss. 5, pp. 1374-1379, 2009.
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H. Yang, P. Bhat, H. Shanahan, and A. Paccanaro
A maximal eigenvalue method for detecting process representative genes by integrating data from multiple sources
in NIPS Workshop on Learning from Multiple Sources, 2008.

A. Devoto and A. Paccanaro
Signal Transduction Networks During Stress Responses in Arabidopsis: High-Throughput Analysis and Modelling
in Plant Growth Signaling, Springer Berlin Heidelberg, 2008, pp. 331-350.

Z. D. Zhang, A. Paccanaro, Y. Fu, S. Weissman, Z. Weng, J. Chang, M. Snyder, and M. B. Gerstein
Statistical analysis of the genomic distribution and correlation of regulatory elements in the ENCODE regions
Genome Research, vol. 17, iss. 6, pp. 787-797, 2007.
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R. D. Waite, A. Paccanaro, A. Papakonstantinopoulou, J. M. Hurst, M. Saqi, E. Littler, and M. A. Curtis
Clustering of Pseudomonas aeruginosa transcriptomes from planktonic cultures, developing and mature biofilms reveals distinct expression profiles
BMC Genomics, vol. 7, iss. 1, p. 162, 2006.
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A. Paccanaro, J. A. Casbon, and M. A. Saqi
Spectral clustering of protein sequences
Nucleic Acids Research, vol. 34, iss. 5, pp. 1571-1580, 2006.
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C. S. Goh, T. A. Gianoulis, Y. Liu, J. Li, A. Paccanaro, Y. A. Lussier, and M. Gerstein
Integration of curated databases to identify genotype-phenotype associations
BMC Genomics, vol. 7, p. 257, 2006.
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H. Yu, A. Paccanaro, V. Trifonov, and M. Gerstein
Predicting interactions in protein networks by completing defective cliques
Bioinformatics, vol. 22, iss. 7, pp. 823-829, 2006.
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R. Sasidharan, M. Gerstein, and A. Paccanaro
Spectral clustering of protein sequences using sequence-profile scores
in Proceedings of ICNPSC 2006 – 3rd International Conference on Neural Parallel and Scientific Computations, 2006.

N. J. Krogan, G. Cagney, H. Yu, G. Zhong, X. Guo, A. Ignatchenko, J. Li, S. Pu, N. Datta, A. P. Tikuisis, T. Punna, J. M. PeregrÃn-Alvarez, M. Shales, X. Zhang, M. Davey, M. D. Robinson, A. Paccanaro, J. E. Bray, A. Sheung, B. Beattie, D. P. Richards, V. Canadien, A. Lalev, F. Mena, P. Wong, A. Starostine, M. M. Canete, J. Vlasblom, S. Wu, C. Orsi, S. R. Collins, S. Chandran, R. Haw, J. J. Rilstone, K. Gandi, N. J. Thompson, G. Musso, P. St Onge, S. Ghanny, M. H. Y. Lam, G. Butland, A. M. Altaf-Ul, S. Kanaya, A. Shilatifard, E. O’Shea, J. S. Weissman, J. C. Ingles, T. R. Hughes, J. Parkinson, M. Gerstein, S. J. Wodak, A. Emili, and J. F. Greenblatt
Global landscape of protein complexes in the yeast Saccharomyces cerevisiae
Nature, vol. 440, iss. 7084, pp. 637-643, 2006.
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M. Seringhaus, A. Paccanaro, A. Borneman, M. Snyder, and M. Gerstein
Predicting essential genes in fungal genomes
Genome Research, vol. 16, iss. 9, pp. 1126-1135, 2006.
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L. J. Lu, Y. Xia, A. Paccanaro, H. Yu, and M. Gerstein
Assessing the limits of genomic data integration for predicting protein networks
Genome Research, vol. 15, iss. 7, pp. 945-953, 2005.
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A. Paccanaro, V. Trifonov, Y. Haiyuan, and M. Gerstein
Inferring protein-protein interactions using interaction network topologies
in Proceedings of the International Joint Conference on Neural Networks, 2005, pp. 161-166.
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A. Paccanaro, C. Chennubhotla, J. A. Casbon, and M. A. S. Saqi
Spectral clustering of protein sequences
in Proceedings of the International Joint Conference on Neural Networks, 2003, pp. 3083-3088.
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C. Chennubhotla and A. Paccanaro
Markov analysis of protein sequence similarities
in Neural nets, 2003, vol. 2859, Springer, pp. 278-286.