TY - GEN
T1 - Combining morphological and migration profiles of in vitro time-lapse data
AU - Becker, Tim
AU - Caicedo, Juan C.
AU - Singh, Shantanu
AU - Weckmann, Markus
AU - Carpenter, Anne E.
N1 - Funding Information:
This work was supported in part by the National Institutes of Health (R35 GM122547 to AEC) and TB was funded by DFG
Funding Information:
Research Fellowship 5728.
Publisher Copyright:
© 2018 IEEE.
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2018/5/23
Y1 - 2018/5/23
N2 - Neutrophil granulocytes belong to the first responders of the innate immune system and are characterized by the capability to migrate towards a site of bacterial infections or inflammation. Several image-based in vitro assays exist to record and quantify their movement using migration parameters like speed, directionality or mean squared displacement. In this work, we propose to add morphological parameters to the analysis of time-lapse data. We analyzed a previously published data set of neutrophil granulocytes and combined morphological and migration profiles using the similarity network fusion (SNF) algorithm. To assess the information (gain) stored in the morphological, migration and combined data, we propose to use the signal strength as an objective measure. We conclude that morphological profiling can be combined with classical migration parameters to improve the readout of in vitro migration assays.
AB - Neutrophil granulocytes belong to the first responders of the innate immune system and are characterized by the capability to migrate towards a site of bacterial infections or inflammation. Several image-based in vitro assays exist to record and quantify their movement using migration parameters like speed, directionality or mean squared displacement. In this work, we propose to add morphological parameters to the analysis of time-lapse data. We analyzed a previously published data set of neutrophil granulocytes and combined morphological and migration profiles using the similarity network fusion (SNF) algorithm. To assess the information (gain) stored in the morphological, migration and combined data, we propose to use the signal strength as an objective measure. We conclude that morphological profiling can be combined with classical migration parameters to improve the readout of in vitro migration assays.
UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85048132655&origin=inward&txGid=b62beaece7648a6cbfce4a28977372ec
U2 - 10.1109/ISBI.2018.8363731
DO - 10.1109/ISBI.2018.8363731
M3 - Conference contribution
SN - 978-1-5386-3637-4
SN - 978-1-5386-3635-0
VL - 2018-April
T3 - Proceedings - International Symposium on Biomedical Imaging
SP - 965
EP - 968
BT - 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)
PB - IEEE
T2 - 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)
Y2 - 4 April 2018 through 7 April 2018
ER -
