Omic signatures of disease are important for personalized treatment because of theheterogeneity of diseases. Despite the advancement of computational tools, there arelimited methods that can capture the latent inter-relationships ...

To truly unlock the advantages of extensive datasets containing individual cell information, like the transcriptome and epigenome, it's crucial to incorporate them and look for ways to label each cell. However, it's a ...

Detection of cancer for diagnosis and tracking the prognosis of the patients using liquid biopsy procedure: the extraction of blood for the detection of cells is the least invasive procedure and relatively fast process ...

Natural selection is a mechanism of evolution, and genetic mutations form the basis of this evolutionary mechanism. With humans migrating out of Africa and inhabiting different parts of the earth, different populations ...

Studying Chromatin Architecture is paramount to an understanding of cells or nuclei in disease and normal state. With recent advances in genomic technologies and computational power, new domains like Topologically associated ...

This project focuses on advancing the precision of disorder detection through the analysis of cell-free DNA signals. By processing Variant Call Format (VCF) files, we employed a Python script to determine mutation rates. ...

Single-cell transcriptomics is a powerful technique that has revolutionized our approach to dissect cellular phenotypes and diversity in complex tissues at an unprecedented res- olution. The emergence of this groundbreaking ...

This research addresses the challenge of network inference in large-scale, sparse datasets. Inspired by the Gini coefficient, we introduce a novel methodology leveraging machine learning, including the GENIE3 algorithm and ...

Epigenetic memory is a vital cellular process. It regulates the inheritance of certain efficient traits of normal cells and the traits attained lately by the cells affected by diseases like Cancer from parents to daughter ...