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Correlations in neural activity can be used to identify such neural modules. Recent technological advances enable us to measure whole-brain neural activity with single-cell resolution in several species including\n                      <jats:inline-formula>\n                        <jats:alternatives>\n                          <jats:tex-math>$$Caenorhabditis\\ elegans$$<\/jats:tex-math>\n                          <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                            <mml:mrow>\n                              <mml:mi>C<\/mml:mi>\n                              <mml:mi>a<\/mml:mi>\n                              <mml:mi>e<\/mml:mi>\n                              <mml:mi>n<\/mml:mi>\n                              <mml:mi>o<\/mml:mi>\n                              <mml:mi>r<\/mml:mi>\n                              <mml:mi>h<\/mml:mi>\n                              <mml:mi>a<\/mml:mi>\n                              <mml:mi>b<\/mml:mi>\n                              <mml:mi>d<\/mml:mi>\n                              <mml:mi>i<\/mml:mi>\n                              <mml:mi>t<\/mml:mi>\n                              <mml:mi>i<\/mml:mi>\n                              <mml:mi>s<\/mml:mi>\n                              <mml:mspace\/>\n                              <mml:mi>e<\/mml:mi>\n                              <mml:mi>l<\/mml:mi>\n                              <mml:mi>e<\/mml:mi>\n                              <mml:mi>g<\/mml:mi>\n                              <mml:mi>a<\/mml:mi>\n                              <mml:mi>n<\/mml:mi>\n                              <mml:mi>s<\/mml:mi>\n                            <\/mml:mrow>\n                          <\/mml:math>\n                        <\/jats:alternatives>\n                      <\/jats:inline-formula>\n                      . Because current neural activity data in\n                      <jats:italic>C. elegans<\/jats:italic>\n                      contain many missing data points, it is necessary to merge results from as many animals as possible to obtain more reliable functional modules.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      In this work, we developed a new time-series clustering method, , to identify functional modules using whole-brain activity data from\n                      <jats:italic>C. elegans<\/jats:italic>\n                      . uses a distance measure, modified shape-based distance to account for the lags and the mutual inhibition of cell\u2013cell interactions and applies the tensor decomposition algorithm multi-view clustering based on matrix integration using the higher orthogonal iteration of tensors (HOOI) algorithm (), which can estimate both the weight to account for the reliability of data from each animal and the clusters that are common across animals.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>\n                      We applied the method to 24 individual\n                      <jats:italic>C. elegans<\/jats:italic>\n                      and successfully found some known functional modules. Compared with a widely used consensus clustering method to aggregate multiple clustering results, showed higher silhouette coefficients. Our simulation also showed that is robust to contamination from noisy data. is freely available as an \/CRAN package\n                      <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/cran.r-project.org\/web\/packages\/WormTensor\">https:\/\/cran.r-project.org\/web\/packages\/WormTensor<\/jats:ext-link>\n                      .\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12859-023-05230-2","type":"journal-article","created":{"date-parts":[[2023,6,16]],"date-time":"2023-06-16T04:03:12Z","timestamp":1686888192000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["WormTensor: a clustering method for time-series whole-brain activity data from C. elegans"],"prefix":"10.1186","volume":"24","author":[{"given":"Koki","family":"Tsuyuzaki","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kentaro","family":"Yamamoto","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yu","family":"Toyoshima","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hirofumi","family":"Sato","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Manami","family":"Kanamori","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Takayuki","family":"Teramoto","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Takeshi","family":"Ishihara","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuichi","family":"Iino","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Itoshi","family":"Nikaido","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,6,16]]},"reference":[{"issue":"3","key":"5230_CR1","doi-asserted-by":"publisher","first-page":"186","DOI":"10.1038\/nrn2575","volume":"10","author":"E Bullmore","year":"2009","unstructured":"Bullmore E, Sporns O. 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