{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,31]],"date-time":"2025-03-31T07:43:42Z","timestamp":1743407022609},"reference-count":37,"publisher":"Oxford University Press (OUP)","issue":"12","license":[{"start":{"date-parts":[[2016,10,2]],"date-time":"2016-10-02T00:00:00Z","timestamp":1475366400000},"content-version":"vor","delay-in-days":2315,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/2.0\/uk\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2010,6,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: High-throughput image-based assay technologies can rapidly produce a large number of cell images for drug screening, but data analysis is still a major bottleneck that limits their utility. Quantifying a wide variety of morphological differences observed in cell images under different drug influences is still a challenging task because the result can be highly sensitive to sampling and noise.<\/jats:p>\n               <jats:p>Results: We propose a graph-based approach to cell image analysis. We define graph transition energy to quantify morphological differences between image sets. A spectral graph theoretic regularization is applied to transform the feature space based on training examples of extremely different images to calibrate the quantification. Calibration is essential for a practical quantification method because we need to measure the confidence of the quantification. We applied our method to quantify the degree of partial fragmentation of mitochondria in collections of fluorescent cell images. We show that with transformation, the quantification can be more accurate and sensitive than that without transformation. We also show that our method outperforms competing methods, including neighbourhood component analysis and the multi-variate drug profiling method by Loo et al. We illustrate its utility with a study of Annonaceous acetogenins, a family of compounds with drug potential. Our result reveals that squamocin induces more fragmented mitochondria than muricin A.<\/jats:p>\n               <jats:p>Availability: Mitochondrial cell images, their corresponding feature sets (SSLF and WSLF) and the source code of our proposed method are available at http:\/\/aiia.iis.sinica.edu.tw\/.<\/jats:p>\n               <jats:p>Contact: \u00a0chunnan@iis.sinica.edu.tw<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btq194","type":"journal-article","created":{"date-parts":[[2010,6,7]],"date-time":"2010-06-07T07:28:13Z","timestamp":1275895693000},"page":"i29-i37","source":"Crossref","is-referenced-by-count":10,"title":["A spectral graph theoretic approach to quantification and calibration of collective morphological differences in cell images"],"prefix":"10.1093","volume":"26","author":[{"given":"Yu-Shi","family":"Lin","sequence":"first","affiliation":[{"name":"1 Institute of Information Science, Academia Sinica, 2 Department of Computer Science and Information Eng., National Taiwan University, 3 Department of Life Science and Institute of Genome Science, National Yang-Ming University, Taipei, 4 Department of Biomedical Engineering, Chung Yuan Christian University, Jhongli, Taiwan and 5 Information Sciences Institute, University of Southern California, Marina del Rey, CA, USA"},{"name":"1 Institute of Information Science, Academia Sinica, 2 Department of Computer Science and Information Eng., National Taiwan University, 3 Department of Life Science and Institute of Genome Science, National Yang-Ming University, Taipei, 4 Department of Biomedical Engineering, Chung Yuan Christian University, Jhongli, Taiwan and 5 Information Sciences Institute, University of Southern California, Marina del Rey, CA, USA"}]},{"given":"Chung-Chih","family":"Lin","sequence":"additional","affiliation":[{"name":"1 Institute of Information Science, Academia Sinica, 2 Department of Computer Science and Information Eng., National Taiwan University, 3 Department of Life Science and Institute of Genome Science, National Yang-Ming University, Taipei, 4 Department of Biomedical Engineering, Chung Yuan Christian University, Jhongli, Taiwan and 5 Information Sciences Institute, University of Southern California, Marina del Rey, CA, USA"}]},{"given":"Yuh-Show","family":"Tsai","sequence":"additional","affiliation":[{"name":"1 Institute of Information Science, Academia Sinica, 2 Department of Computer Science and Information Eng., National Taiwan University, 3 Department of Life Science and Institute of Genome Science, National Yang-Ming University, Taipei, 4 Department of Biomedical Engineering, Chung Yuan Christian University, Jhongli, Taiwan and 5 Information Sciences Institute, University of Southern California, Marina del Rey, CA, USA"}]},{"given":"Tien-Chuan","family":"Ku","sequence":"additional","affiliation":[{"name":"1 Institute of Information Science, Academia Sinica, 2 Department of Computer Science and Information Eng., National Taiwan University, 3 Department of Life Science and Institute of Genome Science, National Yang-Ming University, Taipei, 4 Department of Biomedical Engineering, Chung Yuan Christian University, Jhongli, Taiwan and 5 Information Sciences Institute, University of Southern California, Marina del Rey, CA, USA"}]},{"given":"Yi-Hung","family":"Huang","sequence":"additional","affiliation":[{"name":"1 Institute of Information Science, Academia Sinica, 2 Department of Computer Science and Information Eng., National Taiwan University, 3 Department of Life Science and Institute of Genome Science, National Yang-Ming University, Taipei, 4 Department of Biomedical Engineering, Chung Yuan Christian University, Jhongli, Taiwan and 5 Information Sciences Institute, University of Southern California, Marina del Rey, CA, USA"},{"name":"1 Institute of Information Science, Academia Sinica, 2 Department of Computer Science and Information Eng., National Taiwan University, 3 Department of Life Science and Institute of Genome Science, National Yang-Ming University, Taipei, 4 Department of Biomedical Engineering, Chung Yuan Christian University, Jhongli, Taiwan and 5 Information Sciences Institute, University of Southern California, Marina del Rey, CA, USA"}]},{"given":"Chun-Nan","family":"Hsu","sequence":"additional","affiliation":[{"name":"1 Institute of Information Science, Academia Sinica, 2 Department of Computer Science and Information Eng., National Taiwan University, 3 Department of Life Science and Institute of Genome Science, National Yang-Ming University, Taipei, 4 Department of Biomedical Engineering, Chung Yuan Christian University, Jhongli, Taiwan and 5 Information Sciences Institute, University of Southern California, Marina del Rey, CA, USA"},{"name":"1 Institute of Information Science, Academia Sinica, 2 Department of Computer Science and Information Eng., National Taiwan University, 3 Department of Life Science and Institute of Genome Science, National Yang-Ming University, Taipei, 4 Department of Biomedical Engineering, Chung Yuan Christian University, Jhongli, Taiwan and 5 Information Sciences Institute, University of Southern California, Marina del Rey, CA, USA"}]}],"member":"286","published-online":{"date-parts":[[2010,6,1]]},"reference":[{"key":"2023012508065062200_B1","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1145\/1143844.1143852","article-title":"A new approach to data driven clustering","volume-title":"ICML '06: Proceedings of the 23rd international conference on Machine learning.","author":"Azran","year":"2006"},{"key":"2023012508065062200_B2","doi-asserted-by":"crossref","first-page":"1373","DOI":"10.1162\/089976603321780317","article-title":"Laplacian eigenmaps for dimensionality reduction 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