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Tan, Q. W.

Publications and source records attributed to Tan, Q. W..

2 recordsLinked to original sources

Diurnal.plant.tools: comparative transcriptomic and co-expression analyses of diurnal gene expression of the Archaeplastida kingdom

Almost all organisms coordinate some aspects of their biology through the diurnal cycle. Photosynthetic organisms, and plants especially, have established complex programs that coordinate physiological, metabolic and developmental processes with the changing light. The diurnal regulation of the underlying transcriptional processes is observed when groups of functionally related genes (gene modules) are expressed at a specific time of the day. However, studying the diurnal regulation of these gene modules in the plant kingdom was hampered by the large amount of data required for the analyses. To meet this need, we used gene expression data from 17 diurnal studies spanning the whole Archaeplastida kingdom (Plantae kingdom in the broad sense) to make an online diurnal database. We have equipped the database with tools that allow user-friendly cross-species comparisons of gene expression profiles, entire co-expression networks, co-expressed clusters (involved in specific biological processes), time-specific gene expression, and others. We exemplify how these tools can be used by studying three important biological questions: (i) the evolution of cell division, (ii) the diurnal control of gene modules in algae and (iii) the conservation of diurnally-controlled modules across species. The database is freely available at http://diurnal.plant.tools/.

plant biology

Malaria.tools: comparative genomic and transcriptomic database for Plasmodium species

Malaria is a tropical parasitic disease caused by the Plasmodium genus, which resulted in an estimated 219 million cases of malaria and 435,000 malaria-related deaths in 2017. Despite the availability of the P. falciparum genome since 2002, almost 50% of the genes remain unannotated. To remedy this paucity of functional information, we used transcriptomic data to build gene co-expression networks for two Plasmodium species (P. falciparum and P. berghei), and included genomic data of four other Plasmodium species, P. yoleii, P. knowlesi, P. vivax and P. cynomolgi, as well as two non-Plasmodium species from the Apicomplexa, Toxoplasma gondii and Theileria parva. The database is preloaded with tools that allow the identification and cross-species comparison of co-expressed gene neighborhoods, clusters, and life stage-specific expression, thus providing sophisticated tools to predict gene function. Moreover, we exemplify how the tools can be used to easily identify genes relevant for pathogenicity and various life stages of the malaria parasite. The database is freely available at www.malaria.tools.

bioinformatics