Automatic annotation of spatial expression patterns via sparse bayesian factor models

PLoS Computational Biology

Volumn 7, Issue 7, 2011, Pages

  Pruteanu Malinici, Iulian ^a   Mace, Daniel L ^b   Ohler, Uwe ^a  

^a DUKE UNIVERSITY   (United States)

^b UNIVERSITY OF WASHINGTON   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATIC ANNOTATION; BAYESIAN FACTOR ANALYSIS MODEL; BAYESIAN FACTOR MODELS; EXPRESSION PATTERNS; GENES EXPRESSION; HIGH-DIMENSIONAL IMAGES; LOW RESOLUTION IMAGES; SPARSE BAYESIAN; SPATIAL DYNAMICS; SPATIAL EXPRESSIONS;

GENE EXPRESSION;

DROSOPHILA PROTEIN; RNA;

ARTICLE; AUTOANALYSIS; AUTOMATION; BAYES THEOREM; CONTROLLED STUDY; DEVELOPMENTAL STAGE; GENE EXPRESSION; GENE FUNCTION; GENETIC DATABASE; GENETIC REGULATION; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; MICROSCOPY; RELIABILITY; ALGORITHM; ANIMAL; AREA UNDER THE CURVE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; BIOLOGY; CLUSTER ANALYSIS; DNA MICROARRAY; DROSOPHILA MELANOGASTER; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENETICS; HUMAN; IMAGE PROCESSING; METABOLISM; METHODOLOGY;

ALGORITHMS; ANIMALS; AREA UNDER CURVE; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; CLUSTER ANALYSIS; COMPUTATIONAL BIOLOGY; DROSOPHILA MELANOGASTER; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION, DEVELOPMENTAL; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MODELS, BIOLOGICAL; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PATTERN RECOGNITION, AUTOMATED;

EID: 79960966238     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1002098     Document Type: Article

References (36)

1. Arbeitman MN, Furlong EEM, Imam F, Johnson E, Null BH, et al. (2002) Gene expression during the life cycle of Drosophila melanogaster. Science 297: 2270-2275 doi:10.1126/science.1072152.
2. Hooper SD, Boue S, Krause R, Jensen LJ, Mason CE, et al. (2007) Identification of tightly regulated groups of genes during Drosophila melanogaster embryogenesis. Mol Sys Biol 3 doi:10.1038/msb4100112.
3. Stolc V, Gauhar Z, Mason C, Halasz G, vanBatenburg MF, et al. (2004) A gene expression map for the euchromatic genome of Drosophila melanogaster. Science 306: 655-660 doi:10.1126/science.1101312.
4. Tomancak P, Berman BP, Beaton A, Weiszmann R, Kwan E, et al. (2007) Global analysis of patterns of gene expression during Drosophila embryogenesis. Genome Biol 8 doi:10.1186/gb-2007-8-7-r145.
5. Ljosa V, Carpenter AE, (2009) Introduction to the quantitative analysis of two-dimensional fluorescence microscopy images for cell-based screening. PLoS Comp Biol 5 doi:10.1371/journal.pcbi.1000603.
6. Walter T, Shattuck DW, Baldock R, Bastin ME, Carpenter AE, et al. (2010) Visualization of image data from cells to organisms. Nat Methods 7: 26-41 doi:10.1038/nmeth.1431.
7. Tautz D, Pfeifle C, (1989) A non-radioactive in situ hybridization method for the localization of specific RNAs in Drosophila embryos reveals translational control of the segmentation gene hunchback. Chromosoma 98: 81-85 PMID: 2476281.
8. Tomancak P, Beaton A, Weiszmann R, Kwan E, Hartenstein V, et al. (2002) Systematic determination of patterns of gene expression during Drosophila embryogenesis. Genome Biol 3 doi:10.1186/gb-2002-3-12-research0088.
9. Carson JP, Ju T, Lu HC, Thaller C, Xu M, et al. (2005) A digital atlas to characterize the mouse brain transcriptome. PLoS Comp Biol 1 doi:10.1371/journal.pcbi.0010041.
10. Lein ES, Hawrylycz MJ, Ao N, Ayres M, Bensnger A, et al. (2007) Genome-wide atlas of gene expression in the adult mouse brain. Nature 445: 168-176 doi:10.1038/nature05453.
11. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, et al. (2000) Gene ontology: tool for the unification of biology- The Gene Ontology Consortium. Nat Genet 25: 25-29 doi:10.1038/75556.
12. Chen SC, Zhao T, Gordon GJ, Murphy RF, (2007) Automated image analysis of protein localization in budding yeast. Intel Sys for Mol Biol/European Conf on Comp Biol 23: 66-71 doi:10.1093/bioinformatics/btm206.
13. Kumar S, Jayaraman K, Panchanathan S, Gurunathan R, Marti-Subirana A, et al. (2002) BEST: a novel computational approach for comparing gene expression patterns from early stages of Drosophila melanogaster development. Genetics 162: 2037-2047.
14. Ji S, Li YX, Zhou ZH, Kumar S, Ye J, (2009) A bag-of-words approach for Drosophila gene expression pattern annotation. BMC Bioinformatics 10 doi:10.1186/1471-2105-10-119.
15. Peng H, Long F, Zhou J, Leung G, Eisen MB, et al. (2007) Automatic image analysis for gene expression patterns of fly embryos. BMC Cell Biol 8 doi:10.1186/1471-2121-8-S1-S7.
16. Heffel A, Stadler PF, Prohaska SJ, Kauer G, Kuska JP, (2008) Process flow for classification and clustering of fruit fly gene expression patterns. IEEE Int Conf on Im Proc 1: 721-724 doi:10.1109/ICIP.2008.4711856.
17. Frise E, Hammonds AS, Celniker SE, (2010) Systematic image-driven analysis of the spatial Drosophila embryonic expression landscape. Mol Sys Biol 6 doi:10.1038/msb.2009.102.
18. Pournara I, Wernisch L, (2007) Factor analysis for gene regulatory networks and transcription factor activity profiles. BMC Bioinformatics 8 doi:10.1186/1471-2105-8-61.
19. Mace DL, Varnado N, Zhang W, Frise E, Ohler U, (2010) Extraction and comparison of gene expression patterns from 2D RNA in situ hybridization images. Bioinformatics 26: 761-769 doi:10.1093/bioinformatics/btp658.
20. Adryan B, Teichmann SA, (2006) FlyTF: a systematic review of site-specific transcription factors in the fruit fly Drosophila melanogaster. BMC Bioinformatics 22: 1532-1533 doi:10.1093/bioinformatics/btl143.
21. Roy S, Ernst J, Kharchenko PV, Kheradpour P, Negre N, (2010) Identification of functional elements and regulatory circuits by Drosophila modENCODE. Science 330: 1787-1797 doi:10.1126/science.1198374.
22. Ogienko AA, Karagodin DA, Pavlova NV, Fedorova SA, Voloshina MV, et al. (2008) Molecular and genetic description of a new hypomorphic mutation of Trithorax-like gene and analysis of its effect on Drosophila melanogaster oogenesis. Russian J Dev Biol 39: 108-115 doi:10.1134/S1062360408020070.
23. Sandmann T, Girardot C, Brehme M, Tongprasit W, Stolc V, et al. (2007) A core transcriptional network for early mesoderm development in Drosophila melanogaster. Genes Dev 21: 436-449 doi:10.1101/gad.1509007.
24. Jaebum K, Cunningham R, James B, Wyder S, Gibson JD, et al. (2010) Functional characterization of transcription factor motifs using cross-species comparison across large evolutionary distances. PLoS Comp Biol 6 doi:10.1371/journal.pcbi.1000652.
25. Burges CJC, (1998) A tutorial on support vector machines for pattern recognition. Data Min Knowl Discov 2: 121-167 doi:10.1023/A:1009715923555.
26. Krishnapuram B, Carin L, Figueiredo MAT, Hartemink AJ, (2005) Learning sparse Bayesian classifiers: multi-class formulation, fast algorithms and generalization bounds. IEEE Trans Pattern Anal Mach Intell 27: 957-968 doi:10.1109/TPAMI.2005.127.
27. Gribskov M, Robinson NL, (1996) Use of receiver operating characteristic (ROC) analysis to evaluate sequence matching. Comp Chem 20: 25-33 doi:10.1016/S0097-8485(96)80004-0.
28. Mikolajczyk K, Schmid C, (2005) A performance evaluation of local descriptors. IEEE Trans Pattern Anal Mach Intell 27: 1615-1630 doi:10.1109/TPAMI.2005.188.
29. Pan JY, Balan AGR, Xing EP, Traina AJM, Faloutsos C, (2006) Automatic mining of fruit fly embryo images. Proc of the 12th ACM SIGKDD pp. 693-698 doi:10.1145/1150402.1150489.
30. Puniyani K, Faloutsos C, Xing EP, (2010) SPEX2: automated concise extraction of spatial gene expression patterns from fly embryo ISH images. Bioinformatics 26: i47-i56 doi:10.1093/bioinformatics/btq172.
31. Costa IG, Krause R, Opitz L, Schliep A, (2007) Semi-supervised learning for the identification of syn-expressed genes from fused microarray and in situ image data. BMC Bioinformatics 8 doi:10.1186/1471-2105-8-S10-S3.
32. Gorsuch RL, (1983) Factor analysis Lawrence Erlbaum Associates.
33. Hinton GE, Dayan P, Revow M, (1997) Modeling the manifolds of images of handwritten digits. IEEE Trans on Neural Networks 8: 65-74 doi:10.1109/72.554192.
34. West M, (2003) Bayesian factor regression models in the "large p, small n" paradigm. Bayesian Stat 7: 733-742.
35. Prince SJD, Warrell J, Elder JH, Felisberti FM, (2008) Tied factor analysis for face recognition across large pose differences. IEEE Trans Pattern Anal Mach Intell 30: 970-984 doi:10.1109/TPAMI.2008.48.
36. Joachims T, (1999) Making large-Scale SVM Learning Practical- Advances in Kernel Methods-Support Vector Learning MIT-Press.