{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,26]],"date-time":"2024-07-26T23:06:19Z","timestamp":1722035179746},"reference-count":24,"publisher":"Oxford University Press (OUP)","issue":"18","license":[{"start":{"date-parts":[[2016,10,2]],"date-time":"2016-10-02T00:00:00Z","timestamp":1475366400000},"content-version":"vor","delay-in-days":2220,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/2.0\/uk\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2010,9,15]]},"abstract":"Abstract<\/jats:title>\n Motivation: Nonlinear small datasets, which are characterized by low numbers of samples and very high numbers of measures, occur frequently in computational biology, and pose problems in their investigation. Unsupervised hybrid-two-phase (H2P) procedures\u2014specifically dimension reduction (DR), coupled with clustering\u2014provide valuable assistance, not only for unsupervised data classification, but also for visualization of the patterns hidden in high-dimensional feature space.<\/jats:p>\n Methods: \u2018Minimum Curvilinearity\u2019 (MC) is a principle that\u2014for small datasets\u2014suggests the approximation of curvilinear sample distances in the feature space by pair-wise distances over their minimum spanning tree (MST), and thus avoids the introduction of any tuning parameter. MC is used to design two novel forms of nonlinear machine learning (NML): Minimum Curvilinear embedding (MCE) for DR, and Minimum Curvilinear affinity propagation (MCAP) for clustering.<\/jats:p>\n Results: Compared with several other unsupervised and supervised algorithms, MCE and MCAP, whether individually or combined in H2P, overcome the limits of classical approaches. High performance was attained in the visualization and classification of: (i) pain patients (proteomic measurements) in peripheral neuropathy; (ii) human organ tissues (genomic transcription factor measurements) on the basis of their embryological origin.<\/jats:p>\n Conclusion: MC provides a valuable framework to estimate nonlinear distances in small datasets. Its extension to large datasets is prefigured for novel NMLs. Classification of neuropathic pain by proteomic profiles offers new insights for future molecular and systems biology characterization of pain. Improvements in tissue embryological classification refine results obtained in an earlier study, and suggest a possible reinterpretation of skin attribution as mesodermal.<\/jats:p>\n Availability: \u00a0https:\/\/sites.google.com\/site\/carlovittoriocannistraci\/home<\/jats:p>\n Contact: \u00a0kalokagathos.agon@gmail.com; massimo.alessio@hsr.it<\/jats:p>\n Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btq376","type":"journal-article","created":{"date-parts":[[2010,9,7]],"date-time":"2010-09-07T17:41:46Z","timestamp":1283881306000},"page":"i531-i539","source":"Crossref","is-referenced-by-count":57,"title":["Nonlinear dimension reduction and clustering by Minimum Curvilinearity unfold neuropathic pain and tissue embryological classes"],"prefix":"10.1093","volume":"26","author":[{"given":"Carlo Vittorio","family":"Cannistraci","sequence":"first","affiliation":[{"name":"1 Red Sea Integrative Systems Biology Lab, Computational Bioscience Research Center, Division of Chemical and Life Sciences and Engineering, King Abdullah University for Science and Technology (KAUST), Jeddah, Kingdom of Saudi Arabia, 2Proteome Biochemistry, San Raffaele Scientific Institute, via Olgettina 58, 20132 Milan, 3Department of Mechanics, 4CMP Group, Microsoft Research, Politecnico di Torino, c\/so Duca degli Abruzzi 24, 10129 Turin, Italy, 5Department of Bioengineering and Department of Medicine, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093 USA"},{"name":"1 Red Sea Integrative Systems Biology Lab, Computational Bioscience Research Center, Division of Chemical and Life Sciences and Engineering, King Abdullah University for Science and Technology (KAUST), Jeddah, Kingdom of Saudi Arabia, 2Proteome Biochemistry, San Raffaele Scientific Institute, via Olgettina 58, 20132 Milan, 3Department of Mechanics, 4CMP Group, Microsoft Research, Politecnico di Torino, c\/so Duca degli Abruzzi 24, 10129 Turin, Italy, 5Department of Bioengineering and Department of Medicine, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093 USA"},{"name":"1 Red Sea Integrative Systems Biology Lab, Computational Bioscience Research Center, Division of Chemical and Life Sciences and Engineering, King Abdullah University for Science and Technology (KAUST), Jeddah, Kingdom of Saudi Arabia, 2Proteome Biochemistry, San Raffaele Scientific Institute, via Olgettina 58, 20132 Milan, 3Department of Mechanics, 4CMP Group, Microsoft Research, Politecnico di Torino, c\/so Duca degli Abruzzi 24, 10129 Turin, Italy, 5Department of Bioengineering and Department of Medicine, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093 USA"},{"name":"1 Red Sea Integrative Systems Biology Lab, Computational Bioscience Research Center, Division of Chemical and Life Sciences and Engineering, King Abdullah University for Science and Technology (KAUST), Jeddah, Kingdom of Saudi Arabia, 2Proteome Biochemistry, San Raffaele Scientific Institute, via Olgettina 58, 20132 Milan, 3Department of Mechanics, 4CMP Group, Microsoft Research, Politecnico di Torino, c\/so Duca degli Abruzzi 24, 10129 Turin, Italy, 5Department of Bioengineering and Department of Medicine, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093 USA"},{"name":"1 Red Sea Integrative Systems Biology Lab, Computational Bioscience Research Center, Division of Chemical and Life Sciences and Engineering, King Abdullah University for Science and Technology (KAUST), Jeddah, Kingdom of Saudi Arabia, 2Proteome Biochemistry, San Raffaele Scientific Institute, via Olgettina 58, 20132 Milan, 3Department of Mechanics, 4CMP Group, Microsoft Research, Politecnico di Torino, c\/so Duca degli Abruzzi 24, 10129 Turin, Italy, 5Department of Bioengineering and Department of Medicine, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093 USA"}]},{"given":"Timothy","family":"Ravasi","sequence":"additional","affiliation":[{"name":"1 Red Sea Integrative Systems Biology Lab, Computational Bioscience Research Center, Division of Chemical and Life Sciences and Engineering, King Abdullah University for Science and Technology (KAUST), Jeddah, Kingdom of Saudi Arabia, 2Proteome Biochemistry, San Raffaele Scientific Institute, via Olgettina 58, 20132 Milan, 3Department of Mechanics, 4CMP Group, Microsoft Research, Politecnico di Torino, c\/so Duca degli Abruzzi 24, 10129 Turin, Italy, 5Department of Bioengineering and Department of Medicine, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093 USA"},{"name":"1 Red Sea Integrative Systems Biology Lab, Computational Bioscience Research Center, Division of Chemical and Life Sciences and Engineering, King Abdullah University for Science and Technology (KAUST), Jeddah, Kingdom of Saudi Arabia, 2Proteome Biochemistry, San Raffaele Scientific Institute, via Olgettina 58, 20132 Milan, 3Department of Mechanics, 4CMP Group, Microsoft Research, Politecnico di Torino, c\/so Duca degli Abruzzi 24, 10129 Turin, Italy, 5Department of Bioengineering and Department of Medicine, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093 USA"}]},{"given":"Franco Maria","family":"Montevecchi","sequence":"additional","affiliation":[{"name":"1 Red Sea Integrative Systems Biology Lab, Computational Bioscience Research Center, Division of Chemical and Life Sciences and Engineering, King Abdullah University for Science and Technology (KAUST), Jeddah, Kingdom of Saudi Arabia, 2Proteome Biochemistry, San Raffaele Scientific Institute, via Olgettina 58, 20132 Milan, 3Department of Mechanics, 4CMP Group, Microsoft Research, Politecnico di Torino, c\/so Duca degli Abruzzi 24, 10129 Turin, Italy, 5Department of Bioengineering and Department of Medicine, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093 USA"}]},{"given":"Trey","family":"Ideker","sequence":"additional","affiliation":[{"name":"1 Red Sea Integrative Systems Biology Lab, Computational Bioscience Research Center, Division of Chemical and Life Sciences and Engineering, King Abdullah University for Science and Technology (KAUST), Jeddah, Kingdom of Saudi Arabia, 2Proteome Biochemistry, San Raffaele Scientific Institute, via Olgettina 58, 20132 Milan, 3Department of Mechanics, 4CMP Group, Microsoft Research, Politecnico di Torino, c\/so Duca degli Abruzzi 24, 10129 Turin, Italy, 5Department of Bioengineering and Department of Medicine, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093 USA"}]},{"given":"Massimo","family":"Alessio","sequence":"additional","affiliation":[{"name":"1 Red Sea Integrative Systems Biology Lab, Computational Bioscience Research Center, Division of Chemical and Life Sciences and Engineering, King Abdullah University for Science and Technology (KAUST), Jeddah, Kingdom of Saudi Arabia, 2Proteome Biochemistry, San Raffaele Scientific Institute, via Olgettina 58, 20132 Milan, 3Department of Mechanics, 4CMP Group, Microsoft Research, Politecnico di Torino, c\/so Duca degli Abruzzi 24, 10129 Turin, Italy, 5Department of Bioengineering and Department of Medicine, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093 USA"}]}],"member":"286","published-online":{"date-parts":[[2010,9,4]]},"reference":[{"key":"2023012508282481100_B1","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1126\/science.295.5552.7a","article-title":"The Isomap algorithm and topological stability","volume":"295","author":"Balasubramanian","year":"2002","journal-title":"Science"},{"key":"2023012508282481100_B2","article-title":"Hybrid systems: hidden Markov models and neural networks","volume-title":"Bioinformatics: The Machine Learning 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