BMC Genomics
August 2021
Background: Finding meaningful gene-gene interaction and the main Transcription Factors (TFs) in co-expression networks is one of the most important challenges in gene expression data mining.
Results: Here, we developed the R package "CeTF" that integrates the Partial Correlation with Information Theory (PCIT) and Regulatory Impact Factors (RIF) algorithms applied to gene expression data from microarray, RNA-seq, or single-cell RNA-seq platforms. This approach allows identifying the transcription factors most likely to regulate a given network in different biological systems - for example, regulation of gene pathways in tumor stromal cells and tumor cells of the same tumor.
Non-syndromic intellectual disability (NS-ID or idiopathic) is a complex neurodevelopmental disorder that represents a global health issue. Although many efforts have been made to characterize it and distinguish it from syndromic intellectual disability (S-ID), the highly heterogeneous aspect of this disorder makes it difficult to understand its etiology. Long noncoding RNAs (lncRNAs) comprise a large group of transcripts that can act through various mechanisms and be involved in important neurodevelopmental processes.
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February 2020
Background: The Hereditary Breast and Ovarian Cancer Syndrome (HBOC) occurs in families with a history of breast/ovarian cancer, presenting an autosomal dominant inheritance pattern. BRCA1 and BRCA2 are high penetrance genes associated with an increased risk of up to 20-fold for breast and ovarian cancer. However, only 20-30% of HBOC cases present pathogenic variants in those genes, and other DNA repair genes have emerged as increasing the risk for HBOC.
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