TY - JOUR A1 - Uppaluri, Sravanti A1 - Nagler, Jan A1 - Stellamanns, Eric A1 - Heddergott, Niko A1 - Herminghaus, Stephan A1 - Pfohl, Thomas A1 - Engstler, Markus T1 - Impact of Microscopic Motility on the Swimming Behavior of Parasites: Straighter Trypanosomes are More Directional JF - PLoS Computational Biology N2 - Microorganisms, particularly parasites, have developed sophisticated swimming mechanisms to cope with a varied range of environments. African Trypanosomes, causative agents of fatal illness in humans and animals, use an insect vector (the Tsetse fly) to infect mammals, involving many developmental changes in which cell motility is of prime importance. Our studies reveal that differences in cell body shape are correlated with a diverse range of cell behaviors contributing to the directional motion of the cell. Straighter cells swim more directionally while cells that exhibit little net displacement appear to be more bent. Initiation of cell division, beginning with the emergence of a second flagellum at the base, correlates to directional persistence. Cell trajectory and rapid body fluctuation correlation analysis uncovers two characteristic relaxation times: a short relaxation time due to strong body distortions in the range of 20 to 80 ms and a longer time associated with the persistence in average swimming direction in the order of 15 seconds. Different motility modes, possibly resulting from varying body stiffness, could be of consequence for host invasion during distinct infective stages. KW - African Trypanosomes KW - Cell Motility KW - Random-Walk KW - Brucei KW - Components KW - Flagellum KW - Biology KW - Motion KW - Chemotaxis KW - Movement Y1 - 2011 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-140814 VL - 7 IS - 6 ER - TY - JOUR A1 - Wagner, Toni U. A1 - Fischer, Andreas A1 - Thoma, Eva C. A1 - Schartl, Manfred T1 - CrossQuery: A Web Tool for Easy Associative Querying of Transcriptome Data JF - PLoS ONE N2 - Enormous amounts of data are being generated by modern methods such as transcriptome or exome sequencing and microarray profiling. Primary analyses such as quality control, normalization, statistics and mapping are highly complex and need to be performed by specialists. Thereafter, results are handed back to biomedical researchers, who are then confronted with complicated data lists. For rather simple tasks like data filtering, sorting and cross-association there is a need for new tools which can be used by non-specialists. Here, we describe CrossQuery, a web tool that enables straight forward, simple syntax queries to be executed on transcriptome sequencing and microarray datasets. We provide deep-sequencing data sets of stem cell lines derived from the model fish Medaka and microarray data of human endothelial cells. In the example datasets provided, mRNA expression levels, gene, transcript and sample identification numbers, GO-terms and gene descriptions can be freely correlated, filtered and sorted. Queries can be saved for later reuse and results can be exported to standard formats that allow copy-and-paste to all widespread data visualization tools such as Microsoft Excel. CrossQuery enables researchers to quickly and freely work with transcriptome and microarray data sets requiring only minimal computer skills. Furthermore, CrossQuery allows growing association of multiple datasets as long as at least one common point of correlated information, such as transcript identification numbers or GO-terms, is shared between samples. For advanced users, the object-oriented plug-in and event-driven code design of both server-side and client-side scripts allow easy addition of new features, data sources and data types. KW - Microarray data KW - Sprouting angiogenesis KW - Cell-line KW - Biology Y1 - 2011 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-134787 VL - 6 IS - 12 ER -