Searching journal content for articles similar to Crits-Christoph et al. 31 (2): 239.

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  1. ..., Fischbach MA, et al. 2015. IMG-ABC: a knowledge base to fuel discovery of biosynthetic gene clusters and novel secondary metabolites. MBio 6: e00932-15. doi:10.1128/mBio.00932-15 ↵Huang W, Li L, Myers JR, Marth GT. 2012. ART: a next-generation sequencing read simulator. Bioinformatics 28: 593–594. doi:10...
  2. ...functional diversification during evolution. In this study, we seek to identify the diversification and potential gene neofunctionalization of lung tumors in the TRACERx cohort. We develop a novel computational protocol to identify preduplication and postduplication mutations predicted to affect protein...
  3. ...successfully applied to high-level traits, the prevalence and mode of selection acting on molecular traits remain poorly understood. Here, we estimate the action of natural selection on genetic variants associated with metabolite levels, an important layer of molecular traits. By leveraging summary statistics...
  4. ...Balancing Gene Ontology annotation specificity in protein function prediction 1 based on the protein sequence large graph 2 Jiangyi Shao1,2, Shutao Chen1, Ziwen Wang 1, Zixu Chen1,2, Bin Liu1,2* 3 1 School of Computer Science and Technology, Beijing Institute of Technology, 4 Beijing 100081, China...
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  5. ...that the chimeric mitochondrial transcript frequency also increases and correlates strongly with an orthogonal DNA-based mutation assay performed on identical samples. Further, we show that the frequency of chimeric mitochondrial transcripts predicts expression of both nuclear and mitochondrial genes central...
  6. ...provides the evidence counts for each gene. (B) Predicted repurposable drug candidates by network proximity and GSEA clustered by ATC first-level class. Left panel shows enriched drug candidates identified by network proximity method, in which gradient colors reflect absolute Z-scores. Right panel shows...
  7. ...suboptimally in our ESCC and LUAD_Xing training data sets (AUCPRC 0.028 vs. 0.592 of our gene signature in ESCC and 0.244 vs. 0.513 in LUAD_Xing).Calculation of cancer cell–specific EMT phenotypes using bulk RNA-seq data offers a promising alternative to assess their link with clinical characteristics in cases...
  8. ...downregulated DEGs were enriched in cell adhesion molecules pathways (Supplemental Fig. S5H).To explore the dynamics of gene expression changes with age, we performed clustering analysis of DEGs, identifying distinct groups with varied functions. In oligodendrocytes, for example, we identified four DEG groups...
  9. ...or nuclei and bioinformatic platforms that leverage the power of these data to elucidate regulatory processes have only recently been developed (Reyes et al. 2019; Eisenstein 2020; Chen et al. 2023; Lee et al. 2023; Zhang et al. 2024). Gene expression dynamics, which mediate the biosynthetic tissue...
  10. ...for predicting gene expression (ScPGE) from discrete candidate CREs (cCREs). ScPGE assembles DNA sequences, transcription factor (TF) binding scores, and epigenomic tracks from discrete cCREs into three-dimensional tensors, and then models the relationships between cCREs and genes by combining convolutional...
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