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RNA-seq is a standard method measuring gene regulation using an established set of analysis stages. However, none of the currently available pipeline methods for interpreting ordered genomic data (in time or space) use time-series models to assign cause and effect relationships within GRNs, are adaptive to diverse experimental designs, or enable user interpretation through a web-based platform. Furthermore, methods integrating ordered RNA-seq data with protein\u2013DNA binding data to distinguish direct from indirect interactions are urgently needed. We present TIMEOR (Trajectory Inference and Mechanism Exploration with Omics data in R), the first web-based and adaptive time-series multi-omics pipeline method which infers the relationship between gene regulatory events across time. TIMEOR addresses the critical need for methods to determine causal regulatory mechanism networks by leveraging time-series RNA-seq, motif analysis, protein\u2013DNA binding data, and protein-protein interaction networks. TIMEOR\u2019s user-catered approach helps non-coders generate new hypotheses and validate known mechanisms. We used TIMEOR to identify a novel link between insulin stimulation and the circadian rhythm cycle. TIMEOR is available at https:\/\/github.com\/ashleymaeconard\/TIMEOR.git and http:\/\/timeor.brown.edu.<\/jats:p>","DOI":"10.1093\/nar\/gkab384","type":"journal-article","created":{"date-parts":[[2021,4,28]],"date-time":"2021-04-28T15:53:19Z","timestamp":1619625199000},"page":"W641-W653","source":"Crossref","is-referenced-by-count":21,"title":["TIMEOR: a web-based tool to uncover temporal regulatory mechanisms from multi-omics data"],"prefix":"10.1093","volume":"49","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4143-6180","authenticated-orcid":false,"given":"Ashley Mae","family":"Conard","sequence":"first","affiliation":[{"name":"Computer Science Department, Brown University, Providence, RI 02912, USA"},{"name":"Center for Computational and Molecular Biology, Brown University, Providence, RI 02912, USA"}]},{"given":"Nathaniel","family":"Goodman","sequence":"additional","affiliation":[{"name":"Computer Science Department, Brown University, Providence, RI 02912, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1494-1402","authenticated-orcid":false,"given":"Yanhui","family":"Hu","sequence":"additional","affiliation":[{"name":"Department of Genetics, Harvard Medical School, Boston, MA 02115, USA"},{"name":"Director of Bioinformatics DRSC\/TRiP Functional Genomics Resources, Harvard Medical School, Boston, MA 02115, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7542-472X","authenticated-orcid":false,"given":"Norbert","family":"Perrimon","sequence":"additional","affiliation":[{"name":"Department of Genetics, Harvard Medical School, Boston, MA 02115, USA"},{"name":"Howard Hughes Medical Institute, Harvard Medical School, Boston, MA 02115, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7523-160X","authenticated-orcid":false,"given":"Ritambhara","family":"Singh","sequence":"additional","affiliation":[{"name":"Computer Science Department, Brown University, Providence, RI 02912, USA"},{"name":"Center for Computational and Molecular Biology, Brown University, Providence, RI 02912, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4011-6692","authenticated-orcid":false,"given":"Charles","family":"Lawrence","sequence":"additional","affiliation":[{"name":"Center for Computational and Molecular Biology, Brown University, Providence, RI 02912, USA"},{"name":"Applied Math Department, Brown University, Providence, RI 02912, USA"}]},{"given":"Erica","family":"Larschan","sequence":"additional","affiliation":[{"name":"Center for Computational and Molecular Biology, Brown University, Providence, RI 02912, USA"},{"name":"Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, RI 02912, USA"}]}],"member":"286","published-online":{"date-parts":[[2021,6,14]]},"reference":[{"key":"2021070812185882400_B1","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.compbiomed.2014.02.011","article-title":"A review on the computational approaches for gene regulatory network construction","volume":"48","author":"Chai","year":"2014","journal-title":"Comput. 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