Analyzing and mining automated imaging experiments

Bibliography

• HSU W, LEE ML, ZHANG J: Image mining: trends and developments. J. Intell. Inf. Sys. (2002) 19(1):7-23.
   Web of Science ®Google Scholar
• CHUBB C, INAGAKI Y, COTMAN C, CUMMINGS B, SHEU PC-Y: Semantic biological image management and analysis. Proceedings of the International Conference on Tools with Artificial Intelligence (2003):69-76.
   Google Scholar
• KAPUR R, GIULIANO KA, CAMPANA M et al.: Streamlining the drug discovery process by integrating miniaturization, high throughput screening, high content screening, and automation on the cellchip™ system. Biomed. Microdevices (1999) 2(2):99-109.
   Web of Science ®Google Scholar
• LIU CL, PRAPONG W, NATKUNAM Y et al.: Software tools for high-throughput analysis and archiving of immunohistochemistry staining data obtained with tissue microarrays. Am. J. Pathol. (2002) 161(5):1557-1565.
   PubMed Web of Science ®Google Scholar
• MANLEY S, MUCCI NR, DE MARZO AM, RUBIN MA: Relational database structure to manage high-density tissue microarray data and images for pathology studies focusing on clinical outcome. Am. J. Pathol. (2001) 159(3):837-843.
   PubMed Web of Science ®Google Scholar
• BESKE O, GUO J, LI J et al.: A novel encoded particle technology that enables simultaneous interrogation of multiple cell types. J. Biomol. Screen. (2004) 9(3):173-185.
   PubMed Web of Science ®Google Scholar
• ABRAHAM VC, TAYLOR DL, HASKINS JR: High content screening applied to large-scale cell biology. Trends Biotech. (2004) 22(1):15-22.
   PubMed Web of Science ®Google Scholar
• RAMM P, ALEXANDROV Y, CHOLEWINSKI A, CYBUCH Y, NADON R, SOLTYS BJ: Automated screening of neurite outgrowth. J. Biomol. Screen. (2003) 8(1):7-18.
   PubMed Web of Science ®Google Scholar
• GRÉPIN C, OTROCKA M, ROUX P et al.: Improving quality: high content screening with the Acumen Explorer. Curr. Drug Discov. (2003):37-42.
   Google Scholar
• JÄGER S, GARBOW N, KIRSCH A et al.: A modular, fully integrated ultra-high-throughput screening system based on confocal fluorescence analysis techniques. J. Biomol. Screen. (2003) 8(6):648-659.
   PubMed Web of Science ®Google Scholar
• CARPENTER AE, SABATINI DM: Systematic genome-wide screens of gene function. Nat. Rev. Genet. (2004) 5(1):11-22.
   PubMed Web of Science ®Google Scholar
• ORTIZ DE SOLÓRZANO C, COSTES S, CALLAHAN DE, PARVIN B, BARCELLOS-HOFF MH: Applications of quantitative digital image analysis to breast cancer research. Microsc. Res. Tech. (2002) 59(2):119-127.
   PubMed Web of Science ®Google Scholar
• MARTONE ME, GUPTA A, WONG M et al.: A cell-centered database for electron tomographic data. J. Struct. Biol. (2002) 138(1-2):145-155.
   PubMed Web of Science ®Google Scholar
• SINGH AK, MANJUNATH BS, MURPHY RF: A distributed database for bio-molecular images. SIGMOD Record (2004) 33(2):65-71.
   Google Scholar
• SMEULDERS AWM, WORRING M, SANTINI S, GUPTA A, JAIN R: Content-based image retrieval at the end of the early years. IEEE Transactions on Pattern Analysis and Machine Intelligence (2000) 22(12):1349-1380.
   Google Scholar
• KAM Z, ZAMIR E, GEIGER B: Probing molecular processes in live cells by quantitative multidimensional microscopy. Trends Cell Biol. (2001) 11(8):329-334.
   PubMed Web of Science ®Google Scholar
• RODRÍGUEZ A, GUIL N, SHOTTON DM, TRELLES O: Analysis and description of the semantic content of cell biological videos. Multimedia Tools Applications (2005) 25(1):37-58.
   Web of Science ®Google Scholar
• SHOTTON DM, RODRÍGUEZ A, GUIL N, TRELLES O: Object tracking and event recognition in biological microscopy videos. Proceedings of the 15th International Conference on Pattern Recognition (ICPR) (2000):226-229.
   Google Scholar
• SCHUBERT W: Polymyositis, topological proteomics technology and paradigm for cell invasion dynamics. J. Theor. Med. (2002) 4(1):75-84.
   Google Scholar
• BIBERTHALER P, ATHELOGOU M, LANGER S, LUCHTING B, LEIDERER R, MESSMER K: Evaluation of murine liver transmission electron micrographs by an innovative object-based quantitative image analysis system (Cellenger®). Eur. J. Med. Res. (2003) 8(7):275-282.
   PubMed Web of Science ®Google Scholar
• CAMP RL, CHUNG GG, RIMM DL: Automated subcellular localization and quantification of protein expression in tissue microarrays. Nat. Med. (2002) 8(11):1323-1327.
   PubMed Web of Science ®Google Scholar
• PERLMAN ZE, MITCHISON TJ, MAYER TU: High-content screening and profiling of drug activity in an automated centrosome-duplication assay. ChemBioChem (2005) 6(1):145-151.
   PubMed Web of Science ®Google Scholar
• LIEBEL U, STARKUVIENE V, ERFLE H et al.: A microscope-based screening platform for large-scale functional protein analysis in intact cells. FEBS Lett. (2003) 554(3):394-398.
   PubMed Web of Science ®Google Scholar
• BAGGETT D, NAKAYA M, MCAULIFFE M, YAMAGUCHI TP, LOCKETT S: Whole cell segmentation in solid tissue sections. Cytometry Part A (2005) 67A(2):137-143.
   Web of Science ®Google Scholar
• KASSON PM, HUPPA JB, DAVIS MM, BRUNGER AT: Quantitative analysis of membrane protein localization and signaling. Proceedings of the 2004 IEEE Computational Systems Bioinformatics Conference (2004):540-541.
   Google Scholar
• LI Z, YAN Y, POWERS EA et al.: Identification of gap junction blockers using automated fluorescence microscopy imaging. J. Biomol. Screen. (2003) 8(5):489-499.
   PubMed Web of Science ®Google Scholar
• MATTIE ME, STAIB L, STRATMANN E, TAGARE HD, DUNCAN J, MILLER PL: PathMaster: content-based cell image retrieval using automated feature extraction. J. Am. Med. Inform. Assoc. (2000) 7(4):404-415.
   PubMed Web of Science ®Google Scholar
• YARROW JC, PERLMAN ZE, WESTWOOD NJ, MITCHISON TJ: A high-throughput cell migration assay using scratch wound healing, a comparison of image-based readout methods. BMC Biotechnol. (2004) 4:21.
   PubMed Web of Science ®Google Scholar
• BRINKMANN M, LÜTKEMEYER D, GUDERMANN F, LEHMANN J: New technologies for automated cell counting based on optical image analysis ‘the Cellscreen’. Cytotechnology (2002) 38(1-3):119-127.
   PubMed Web of Science ®Google Scholar
• ZAIDI SK, YOUNG DW, POCKWINSE SM et al.: Mitotic partitioning and selective reorganization of tissue-specific transcription factors in progeny cells. Proc. Natl. Acad. Sci. USA (2003) 100(25):14852-14857.
   PubMed Web of Science ®Google Scholar
• HUANG K, MURPHY RF: From quantitative microscopy to automated image understanding. J. Biomed. Optics (2004) 9(5):893-912.
   PubMed Web of Science ®Google Scholar
• MURPHY RF, VELLISTE M, PORRECA G: Robust numerical features for description and classification of subcellular location patterns in fluorescence microscope images. J. VLSI Signal Processing (2003) 35(3):311-321.
   Google Scholar
• COSTA LDF, CINTRA LC, SCHUBERT D: An integrated approach to the characterization of cell movement. Cytometry Part A (2005) 68A(2):92-100.
   Web of Science ®Google Scholar
• DUDA RO, HART. PE, STORK DG: Pattern Classification. Wiley, NY (2000).
   Google Scholar
• KUMAR A, AGARWAL S, HEYMAN JA et al.: Subcellular localization of the yeast proteome. Genes Dev. (2002) 16(6):707-719.
   PubMed Web of Science ®Google Scholar
• ZHENG Q, MILTHORPE BK, JONES AS: Direct neural network application for automated cell recognition. Cytometry Part A (2004) 57A(1):1-9.
   Web of Science ®Google Scholar
• MAGLOGIANNIS IG, ZAFIROPOULOS EP: Characterization of digital medical images utilizing support vector machines. BMC Med. Inf. and Decision Making (2004) 4:1-9.
   PubMedGoogle Scholar
• PRICE JH, GOODACRE A, HAHN K et al.: Advances in molecular labeling, high throughput imaging and machine intelligence portend powerful functional cellular biochemistry tools. J. Cell. Biochem. (2002) (Suppl. 39):194-210.
   PubMedGoogle Scholar
• PERNER P, PERNER H, BÜHRING A, JÄNICHEN S: Mining images to find general forms of biological objects. Lecture Notes in Artificial Intelligence 3275 (2004):60-68.
   Google Scholar
• CONRAD C, ERFLE H, WARNAT P et al.: Automatic identification of subcellular phenotypes on human cell arrays. Genome Res. (2004) 14:1130-1136.
   PubMed Web of Science ®Google Scholar
• HUANG K, MURPHY RF: Boosting accuracy of automated classification of fluorescence microscope images for location proteomics. BMC Bioinformatics (2004) 5:78.
   PubMedGoogle Scholar
• MITCHISON TJ: Small-molecule screening and profiling by using automated microscopy. ChemBioChem (2005) 6(1):33-39.
   PubMed Web of Science ®Google Scholar
• KEIM DA: Visual exploration of large data sets. Communications of the ACM (2001) 44(8):39-44.
   Google Scholar
• SHNEIDERMAN B: Eyes have it: a task by data type taxonomy for information visualizations. Proceedings – IEEE Symposium on Visual Languages (1996):336-343.
   Google Scholar
• CURTIS J, HUESING J, SIMPSON R, ELANDS J: Information management for entomology screening. J. Biomol. Screen. (2004) 9(1):37-43.
   PubMed Web of Science ®Google Scholar
• DIALLO B, DOLIDON F, TRAVERE J-M, MAZOYER B: B-SPID: an object-relational database architecture to store, retrieve, and manipulate neuroimaging data. Hum. Brain Mapping (1999) 7(2):136-150.
   PubMed Web of Science ®Google Scholar
• MÜLLER H, MICHOUX N, BANDON D, GEISSBUHLER A: A review of content-based image retrieval systems in medical applications – clinical benefits and future directions. Int. J. Med. Inf. (2004) 73(1):1-23.
   PubMed Web of Science ®Google Scholar
• SPENKE M: Visualization and interactive analysis of blood parameters with InfoZoom. Artif. Intell. Med. (2001) 22(2):159-172.
   PubMed Web of Science ®Google Scholar
• SPENKE M, BEILKEN C: Visualization of trees as highly compressed tables with InfoZoom. Proceedings – IEEE Symposium on Information Visualization INFO VIS (2003):122-123.
   Google Scholar
• SARAIYA P, NORTH C, DUCA K: An evaluation of microarray visualization tools for biological insight. Proceedings – IEEE Symposium on Information Visualization INFO VIS (2004):1-8.
   Google Scholar
• PERLMAN ZE, SLACK MD, FENG Y, MITCHISON TJ, WU LF, ALTSCHULER SJ: Multidimensional drug profiling by automated microscopy. Science (2004) 306(5699):1194-1198.
   PubMed Web of Science ®Google Scholar
• GÜLD MO, KOHNEN M, KEYSERS D et al.: Quality of DICOM header information for image categorization. Proceedings of SPIE – The International Society for Optical Engineering (2002) 4685:280-287.
   Google Scholar
• DIREEN HG, JONES MS: Knowledge management in bioinformatics. In: XML Data Management. Chaudhri AB et al. (Eds.), Addison Wesley (2003).
   Google Scholar
• SWEDLOW JR, GOLDBERG I, BRAUNER E, SORGER PK: Informatics and quantitative analysis in biological imaging. Science (2003) 300(5616):100-102.
   PubMed Web of Science ®Google Scholar
• NEUMANN E, THOMAS J: Knowledge assembly for the life sciences. Drug Discov. Today (2002) 7(20):S160-S162.
   PubMed Web of Science ®Google Scholar
• BERMAN JJ, EDGERTON ME, FRIEDMAN BA: The tissue microarray data exchange specification: a community-based, open source tool for sharing tissue microarray data. BMC Med. Inf. Dec. Making (2003) 3:1-9.
   PubMedGoogle Scholar
• CLARK T, MARTIN S, LIEFELD T: Globally distributed object identification for biological knowledgebases. Brief. Bioinformatics (2004) 5(1):59-70.
   PubMed Web of Science ®Google Scholar
• DE ROURE D, HENDLER JA: E-Science: the Grid and the Semantic Web. IEEE Intelligent Systems (2004) 19(1):65-71.
   Web of Science ®Google Scholar
• MANGO LJ: Computer-assisted cervical cancer screening using neural networks. Cancer Lett. (1994) 77(2-3):155-162.
   PubMed Web of Science ®Google Scholar
• PERNER P, PERNER H, MÜLLER B: Mining knowledge for HEp-2 cell image classification. Artif. Intell. Med. (2002) 26(1-2):161-173.
   PubMed Web of Science ®Google Scholar
• GERSTNER A, TRUMPFHELLER C, RACZ P, OSMANCIK P, TENNER-RACZ K, TÁRNOK A: Quantitative histology by multicolor slide-based cytometry. Cytometry Part A (2004) 59A(2):210-219.
   Web of Science ®Google Scholar
• SAYEED A, PETROU M, SPYROU N, KADYROV A, SPINKS T: Diagnostic features of Alzheimer’s disease extracted from PET sinograms. Phys. Med. Biol. (2002) 47(1):137-148.
   PubMed Web of Science ®Google Scholar
• KEYSERS D, DAHMEN J, NEY H, WEIN BB, LEHMANN TM: Statistical framework for model-based image retrieval in medical applications. J. Electronic Imaging (2003) 12(1):59-68.
   Web of Science ®Google Scholar
• SMITH AE, SLEPCHENKO BM, SCHAFF JC, LOEW LM, MACARA IG: Systems analysis of Ran transport. Science (2002) 295(5554):488-491.
   PubMed Web of Science ®Google Scholar
• HARADA JN, BOWER KE, ORTH AP et al.: Identification of novel mammalian growth regulatory factors by genome-scale quantitative image analysis. Genome Res. (2005) 15(8):1136-1144.
   PubMed Web of Science ®Google Scholar
• STARKUVIENE V, LIEBEL U, SIMPSON JC et al.: High-content screening microscopy identifies novel proteins with a putative role in secretory membrane traffic. Genome Res. (2004) 14(10A):1948-1956.
   PubMed Web of Science ®Google Scholar
• ZHOU X, CAO X, PERLMAN Z, WONG STC: A computerized cellular imaging system for high content analysis in Monastrol suppressor screens. J. Biomed. Informatics (2006) 39(2):115-125.
   PubMed Web of Science ®Google Scholar
• BHAWE KM, BLAKE RA, CLARY DO, FLANAGAN PM: An automated image capture and quantitation approach to identify proteins affecting tumor cell proliferation. J. Biomol. Screen. (2004) 9(3):216-222.
   PubMed Web of Science ®Google Scholar
• HASTINGS S, OSTER S, LANGELLA S et al.: A grid based image archival and analysis system. J. Am. Med. Inform. Assoc. (2005) 12(3):286-295.
   PubMed Web of Science ®Google Scholar