Biology subjects

Oluwadare, O. E.

Publications and source records attributed to Oluwadare, O. E..

4 recordsLinked to original sources

bioRxiv2025

Robin: An Advanced Tool for Comparative Loop Caller Result Analysis Leveraging Large Language Models

BackgroundThere has been significant interest in genomics research, leading to the development of numerous new methods. One notable area of progress is in chromosome looping detection algorithms (also known as loop callers). However, despite these advancements, there is no available platform to analyze, compare, or benchmark current tools results on the go. Developing such a platform is crucial to accelerate research and ensure the reliability and effectiveness of new methods in the field. ResultsHence, in this work, we propose Robin, an advanced ready-to-go platform for comparative loop caller result analysis leveraging Large Language Models (LLMs). Robin is a web server designed to analyze loop caller results, offering a comprehensive range of analysis metrics such as recovery and overlap. It is integrated with HiGlass and incorporates LLMs to enable users to generate plots simply by providing instructions. ConclusionsOverall, Robin is a robust and comprehensive loop caller result analysis and visualization tool. It is publicly accessible at http://hicrobin.online, with a comprehensive documentation available at http://documentation.hicrobin.online/.

bioinformatics↗

bioRxiv2024

DiCARN-DNase: Enhancing Cell-to-Cell Hi-C Resolution Using Dilated Cascading ResNet with Self-Attention and DNase-seq Chromatin Accessibility Data

The spatial organization of chromatin is fundamental to gene regulation and essential for proper cellular function. The Hi-C technique remains the leading method for unraveling 3D genome structures, but the limited availability of high-resolution Hi-C data poses significant challenges for comprehensive analysis. Deep learning models have been developed to predict high-resolution Hi-C data from low-resolution counterparts. Early CNN-based models improved resolution but struggled with issues like blurring and capturing fine details. In contrast, GAN-based methods encountered difficulties in maintaining diversity and generalization. Additionally, most existing algorithms perform poorly in cross-cell line generalization, where a model trained on one cell type is used to enhance high-resolution data in another cell type. In this work, we propose DiCARN (Dilated Cascading Residual Network) to overcome these challenges and improve Hi-C data resolution. DiCARN leverages dilated convolutions and cascading residuals to capture a broader context while preserving fine-grained genomic interactions. Additionally, we incorporate DNase-seq data into our model, providing a robust framework that demonstrates superior generalizability across cell lines in high-resolution Hi-C data reconstruction. DiCARN is publicly available at https://github.com/OluwadareLab/DiCARN

bioinformatics↗

bioRxiv2024

A Constitutive Heterochromatic Region Shapes Genome Organization and Impacts Gene Expression in Neurospora crassa

BackgroundOrganization of the eukaryotic genome is essential for proper function, including gene expression. In metazoans, chromatin loops and Topologically Associated Domains (TADs) organize genes into transcription factories, while chromosomes occupy nuclear territories in which silent heterochromatin is compartmentalized at the nuclear periphery and active euchromatin localizes to the nucleus center. A similar hierarchical organization occurs in the fungus Neurospora crassa where its seven chromosomes form a Rabl conformation typified by heterochromatic centromeres and telomeres independently clustering at the nuclear membrane, while interspersed heterochromatic loci aggregate across Megabases of linear genomic distance to loop chromatin in TAD-like structures. However, the role of individual heterochromatic loci in normal genome organization and function is unknown. ResultsWe examined the genome organization of a Neurospora strain harboring a [~]47.4 kilobase deletion within a temporarily silent, facultative heterochromatic region, as well as the genome organization of a strain deleted of a 110.6 kilobase permanently silent constitutive heterochromatic region. While the facultative heterochromatin deletion minimally effects local chromatin structure or telomere clustering, the constitutive heterochromatin deletion alters local chromatin structure, the predicted three-dimensional chromosome conformation, and the expression of some genes, which are qualitatively repositioned into the nucleus center, while increasing Hi-C variability. ConclusionsOur work elucidates how an individual constitutive heterochromatic region impacts genome organization and function. Specifically, one silent region indirectly assists in the hierarchical folding of the entire Neurospora genome by aggregating into the "typical" heterochromatin bundle normally observed in wild type nuclei, which may promote normal gene expression by positioning euchromatin in the nucleus center.

genomics↗

bioRxiv2019

GSDB: a database of 3D chromosome and genome structures reconstructed from Hi-C data

Advances in the study of chromosome conformation capture (3C) technologies, such as Hi-C technique - capable of capturing chromosomal interactions in a genome-wide scale - have led to the development of three-dimensional (3D) chromosome and genome structure reconstruction methods from Hi-C data. The 3D genome structure is important because it plays a role in a variety of important biological activities such as DNA replication, gene regulation, genome interaction, and gene expression. In recent years, numerous Hi-C datasets have been generated, and likewise, a number of genome structure construction algorithms have been developed. However, until now, there has been no freely available repository for 3D chromosome structures. In this work, we outline the construction of a novel Genome Structure Database (GSDB) to create a comprehensive repository that contains 3D structures for Hi-C datasets constructed by a variety of 3D structure reconstruction tools. GSDB contains over 50,000 structures constructed by 12 state-of-the-art chromosome and genome structure prediction methods for publicly used Hi-C datasets with varying resolution. The database is useful for the community to study the function of genome from a 3D perspective. GSDB is accessible at http://sysbio.rnet.missouri.edu/3dgenome/GSDB

bioinformatics↗