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- W4386001194 abstract "Elucidating gene function is a major goal in biology, especially among non-model organisms. However, doing so is complicated by the fact that molecular conservation does not always mirror functional conservation, and that complex relationships among genes are responsible for encoding pathways and higher-order biological processes. Co-expression, a promising approach for predicting gene function, relies on the general principal that genes with similar expression patterns across multiple conditions will likely be involved in the same biological process. For Cryptococcus neoformans, a prevalent human fungal pathogen greatly diverged from model yeasts, approximately 60% of the predicted genes in the genome lack functional annotations. Here, we leveraged a large amount of publicly available transcriptomic data to generate a C. neoformans Co-Expression Network (CryptoCEN), successfully recapitulating known protein networks, predicting gene function, and enabling insights into the principles influencing co-expression. With 100% predictive accuracy, we used CryptoCEN to identify 13 new DNA damage response genes, underscoring the utility of guilt-by-association for determining gene function. Overall, co-expression is a powerful tool for uncovering gene function, and decreases the experimental tests needed to identify functions for currently under-annotated genes." @default.
- W4386001194 created "2023-08-20" @default.
- W4386001194 creator A5026029793 @default.
- W4386001194 creator A5035962186 @default.
- W4386001194 creator A5037269824 @default.
- W4386001194 creator A5040186906 @default.
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- W4386001194 creator A5054548015 @default.
- W4386001194 creator A5056540163 @default.
- W4386001194 creator A5071152958 @default.
- W4386001194 date "2023-08-18" @default.
- W4386001194 modified "2023-10-07" @default.
- W4386001194 title "CryptoCEN: A Co-Expression Network for<i>Cryptococcus neoformans</i>reveals novel proteins involved in DNA damage repair" @default.
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