We present the PATHOgenic YEAst Search for Transcriptional Regulators And Consensus Tracking (PathoYeastract - http://pathoyeastract.org) database, a tool for the analysis and prediction of transcription regulatory associations at the gene and genomic levels in the pathogenic yeasts Candida albicans and C. glabrata Upon data retrieval from hundreds of publications, followed by curation, the database currently includes 28 000 unique documented regulatory associations between transcription factors (TF) and target genes and 107 DNA binding sites, considering 134 TFs in both species. Following the structure used for the YEASTRACT database, PathoYeastract makes available bioinformatics tools that enable the user to exploit the existing information to predict the TFs involved in the regulation of a gene or genome-wide transcriptional response, while ranking those TFs in order of their relative importance. Each search can be filtered based on the selection of specific environmental conditions, experimental evidence or positive/negative regulatory effect. Promoter analysis tools and interactive visualization tools for the representation of TF regulatory networks are also provided. The PathoYeastract database further provides simple tools for the prediction of gene and genomic regulation based on orthologous regulatory associations described for other yeast species, a comparative genomics setup for the study of cross-species evolution of regulatory networks.
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http://dx.doi.org/10.1093/nar/gkw817 | DOI Listing |
Int J Syst Evol Microbiol
January 2025
College of Life Sciences and Medicine, Zhejiang Sci-Tech University, Hangzhou 310018, PR China.
A Gram-stain-negative, aerobic and rod-shaped bacterium, designated as HZG-20, was isolated from a tidal flat in Zhoushan, Zhejiang Province, China. The 16S rRNA sequence similarities between strain HZG-20 and RR4-56, NNCM2, P31 and X9-2-2 were 98.9, 91.
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Medical Genetics, Department of Health Sciences, Università degli Studi di Milano, Milan, Italy.
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West China School of Medicine, Sichuan University, Chengdu, China.
Gastric cancer is an aggressive malignancy characterized by significant clinical heterogeneity arising from complex genetic and environmental interactions. This study employed single-cell RNA sequencing, using the 10 × Genomics platform, to analyze 262,532 cells from gastric cancer samples, identifying 32 distinct clusters and 10 major cell types, including immune cells (e.g.
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Department of Marine Science and Technology, Fukui Prefectural University, Obama, Fukui, 917-0003, Japan.
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