Code from: STRAINS: A Big Data Method for Classifying Cellular Response to Stimuli at the Tissue Scale
| dc.contributor.author | Zheng, Jingyang | |
| dc.contributor.author | Wyse Jackson, Thomas | |
| dc.contributor.author | Fortier, Lisa | |
| dc.contributor.author | Bonassar, Lawrence | |
| dc.contributor.author | Delco, Michelle | |
| dc.contributor.author | Cohen, Itai | |
| dc.date.accessioned | 2022-08-06T20:27:42Z | |
| dc.date.available | 2022-08-06T20:27:42Z | |
| dc.date.issued | 2022-08-06 | |
| dc.description | This code shared under a MIT License Copyright 2022 Jingyang Zheng Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: attribution to the copyright holder (Jingyang Zheng) and citation of the associated publication (https://www.biorxiv.org/content/10.1101/2022.06.12.495830v2), and email the copyright holder (jz848@cornell.edu) so that the copyright holder can share and cite examples of adaptations The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. | en_US |
| dc.description | Please cite as: Zheng, Jingyang, Thomas Wyse Jackson, Lisa Fortier, Lawrence Bonassar, Michelle Delco, and Itai Cohen (2022). Code from: STRAINS: A Big Data Method for Classifying Cellular Response to Stimuli at the Tissue Scale [Source Code] Cornell University Library eCommons Digital Repository. https://doi.org/10.7298/ds7s-nc16 | |
| dc.description.abstract | These files contain data supporting all results reported in Zheng et. al., STRAINS: A Big Data Method for Classifying Cellular Response to Stimuli at the Tissue Scale. Cellular response to stimulation governs tissue scale processes ranging from growth and development to maintaining tissue health and initiating disease. To determine how cells coordinate their response to such stimuli, it is necessary to simultaneously track and measure the spatiotemporal distribution of their behaviors throughout the tissue. Here, we report on a novel SpatioTemporal Response Analysis IN Situ (STRAINS) tool that uses fluorescent micrographs, cell tracking, and machine learning to measure such behavioral distributions. STRAINS is broadly applicable to any tissue where fluorescence can be used to indicate changes in cell behavior. For illustration, we use STRAINS to simultaneously analyze the mechanotransduction response of 5000 chondrocytes---over 20 million data points---in cartilage during the 50 ms to 4 hours after the tissue was subjected to local mechanical injury, known to initiate osteoarthritis. We find that chondrocytes exhibit a range of mechanobiological responses indicating activation of distinct biochemical pathways with clear spatial patterns related to the induced local strains during impact. These results illustrate the power of this approach. | en_US |
| dc.description.sponsorship | The work was supported by the NIH National Institute of Arthritis and Musculoskeletal and Skin Diseases, Contract: 5R01AR071394-04, K08AR068470, R03AR075929, and The Harry M. Zweig Fund for Equine Research. Additionally, this work was supported by the National Science Foundation grants DMR-1807602, DMR-1808026, CBET-1604712, CMMI 1927197, and BMMB-1536463. Lastly, this work made use of the Cornell Center for Materials Research Shared Facilities which are supported through the NSF MRSEC program (DMR-1719875). | en_US |
| dc.identifier.doi | https://doi.org/10.7298/ds7s-nc16 | |
| dc.identifier.uri | https://hdl.handle.net/1813/111392 | |
| dc.language.iso | en_US | en_US |
| dc.relation | Zheng, Jingyang, Thomas Wyse Jackson, Lisa Fortier, Lawrence Bonassar, Michelle Delco, and Itai Cohen (2022). Data from: STRAINS: A Big Data Method for Classifying Cellular Response to Stimuli at the Tissue Scale [Dataset] Cornell University Library eCommons Digital Repository. https://doi.org/10.7298/3kwt-pm43 | |
| dc.relation.isreferencedby | Zheng, J., Wyse Jackson, T., Fortier, L. A., Bonassar, L. J., Delco, M. L., & Cohen, I. (2022). STRAINS: A big data method for classifying cellular response to stimuli at the tissue scale. PLOS ONE, 17(12), e0278626. https://doi.org/10.1371/journal.pone.0278626 | |
| dc.relation.isreferencedbyuri | https://doi.org/10.1371/journal.pone.0278626 | |
| dc.relation.uri | https://doi.org/10.7298/3kwt-pm43 | |
| dc.subject | Mechanotransduction | en_US |
| dc.subject | machine learning | en_US |
| dc.subject | time series classification | en_US |
| dc.subject | cartilage injury | en_US |
| dc.title | Code from: STRAINS: A Big Data Method for Classifying Cellular Response to Stimuli at the Tissue Scale | en_US |
| dc.type | software | en_US |