Gene expression patterns determine the differential numbers of dorsocentral macrochaetes between Musca domestica and Drosophila melanogaster

genesis ◽  
2018 ◽  
Vol 56 (11-12) ◽  
pp. e23258
Author(s):  
Qing Liang ◽  
Tingting Peng ◽  
Boyuan Sun ◽  
Jianbo Tu ◽  
Xingyi Cheng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Drosophila Melanogaster ◽  
Musca Domestica ◽  
Expression Patterns ◽  
Gene Expression Patterns

scholarly journals BEST: A Novel Computational Approach for Comparing Gene Expression Patterns From Early Stages of Drosophila melanogaster Development

Genetics ◽  
2002 ◽  
Vol 162 (4) ◽  
pp. 2037-2047
Author(s):  
Sudhir Kumar ◽  
Karthik Jayaraman ◽  
Sethuraman Panchanathan ◽  
Rajalakshmi Gurunathan ◽  
Ana Marti-Subirana ◽  
...  
Keyword(s):  
Gene Expression ◽  
Developmental Biology ◽  
Drosophila Melanogaster ◽  
Expression Pattern ◽  
Early Stage ◽  
Expression Patterns ◽  
Gene Expression Pattern ◽  
Computational Approach ◽  
Gene Expression Patterns ◽  
Early Stages

Abstract Embryonic gene expression patterns are an indispensable part of modern developmental biology. Currently, investigators must visually inspect numerous images containing embryonic expression patterns to identify spatially similar patterns for inferring potential genetic interactions. The lack of a computational approach to identify pattern similarities is an impediment to advancement in developmental biology research because of the rapidly increasing amount of available embryonic gene expression data. Therefore, we have developed computational approaches to automate the comparison of gene expression patterns contained in images of early stage Drosophila melanogaster embryos (prior to the beginning of germ-band elongation); similarities and differences in gene expression patterns in these early stages have extensive developmental effects. Here we describe a basic expression search tool (BEST) to retrieve best matching expression patterns for a given query expression pattern and a computational device for gene interaction inference using gene expression pattern images and information on the associated genotypes and probes. Analysis of a prototype collection of Drosophila gene expression pattern images is presented to demonstrate the utility of these methods in identifying biologically meaningful matches and inferring gene interactions by direct image content analysis. In particular, the use of BEST searches for gene expression patterns is akin to that of BLAST searches for finding similar sequences. These computational developmental biology methodologies are likely to make the great wealth of embryonic gene expression pattern data easily accessible and to accelerate the discovery of developmental networks.

scholarly journals larvalign: Aligning Gene Expression Patterns from the Larval Brain of Drosophila melanogaster

2017 ◽  
Vol 16 (1) ◽  
pp. 65-80 ◽  
Author(s):  
Sascha E. A. Muenzing ◽  
Martin Strauch ◽  
James W. Truman ◽  
Katja Bühler ◽  
Andreas S. Thum ◽  
...  
Keyword(s):  
Gene Expression ◽  
Drosophila Melanogaster ◽  
Expression Patterns ◽  
Gene Expression Patterns ◽  
Larval Brain

Gene expression patterns in blood predict future severe endpoints in community acquired pneumonia

Pneumologie ◽  
2018 ◽  
Vol 72 (S 01) ◽  
pp. S8-S9
Author(s):  
M Bauer ◽  
H Kirsten ◽  
E Grunow ◽  
P Ahnert ◽  
M Kiehntopf ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Patterns ◽  
Community Acquired Pneumonia ◽  
Gene Expression Patterns
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