Výsledky vyhledávání

Akademický článek

Cross‐Species Prediction of Transcription Factor Binding by Adversarial Training of a Novel Nucleotide‐Level Deep Neural Network

Autor: Qinhu Zhang, Siguo Wang, Zhipeng Li, Yijie Pan, De‐Shuang Huang

Publikováno v: Advanced Science, Vol 11, Iss 36, Pp n/a-n/a (2024)

Abstract Cross‐species prediction of TF binding remains a major challenge due to the rapid evolutionary turnover of individual TF binding sites, resulting in cross‐species predictive performance being consistently worse than within‐species perf

Externí odkaz: https://doaj.org/article/e8e5949bd0dd41db8b4a321930fe9d74

Zobrazit plný text záznamu

Plný text ve formátu HTML

Akademický článek

scInterpreter: a knowledge-regularized generative model for interpretably integrating scRNA-seq data

Autor: Zhen-Hao Guo, Yan Wu, Siguo Wang, Qinhu Zhang, Jin-Ming Shi, Yan-Bin Wang, Zhan-Heng Chen

Publikováno v: BMC Bioinformatics, Vol 24, Iss 1, Pp 1-14 (2023)

Abstract Background The rapid emergence of single-cell RNA-seq (scRNA-seq) data presents remarkable opportunities for broad investigations through integration analyses. However, most integration models are black boxes that lack interpretability or ar

Externí odkaz: https://doaj.org/article/4b1520acd296408fa75366a0387eae14

Zobrazit plný text záznamu

Plný text ve formátu HTML

Akademický článek

Nucleotide-level prediction of CircRNA-protein binding based on fully convolutional neural network

Autor: Zhen Shen, Wei Liu, ShuJun Zhao, QinHu Zhang, SiGuo Wang, Lin Yuan

Publikováno v: Frontiers in Genetics, Vol 14 (2023)

Introduction: CircRNA-protein binding plays a critical role in complex biological activity and disease. Various deep learning-based algorithms have been proposed to identify CircRNA-protein binding sites. These methods predict whether the CircRNA seq

Externí odkaz: https://doaj.org/article/cf114b82a6454fcf9f410f737cb5deae

Zobrazit plný text záznamu

Akademický článek

DLoopCaller: A deep learning approach for predicting genome-wide chromatin loops by integrating accessible chromatin landscapes.

Autor: Siguo Wang, Qinhu Zhang, Ying He, Zhen Cui, Zhenghao Guo, Kyungsook Han, De-Shuang Huang

Publikováno v: PLoS Computational Biology, Vol 18, Iss 10, p e1010572 (2022)

In recent years, major advances have been made in various chromosome conformation capture technologies to further satisfy the needs of researchers for high-quality, high-resolution contact interactions. Discriminating the loops from genome-wide conta

Externí odkaz: https://doaj.org/article/3bcafffea78c49c3879f32854d356c14

Zobrazit plný text záznamu

Plný text ve formátu HTML

Akademický článek

Predicting transcription factor binding sites using DNA shape features based on shared hybrid deep learning architecture

Autor: Siguo Wang, Qinhu Zhang, Zhen Shen, Ying He, Zhen-Heng Chen, Jianqiang Li, De-Shuang Huang

Publikováno v: Molecular Therapy: Nucleic Acids, Vol 24, Iss , Pp 154-163 (2021)

The study of transcriptional regulation is still difficult yet fundamental in molecular biology research. Recent research has shown that the double helix structure of nucleotides plays an important role in improving the accuracy and interpretability

Externí odkaz: https://doaj.org/article/5613196c730b47b7815fd2001efb451c

Zobrazit plný text záznamu

Akademický článek

Base-resolution prediction of transcription factor binding signals by a deep learning framework.

Autor: Qinhu Zhang, Ying He, Siguo Wang, Zhanheng Chen, Zhenhao Guo, Zhen Cui, Qi Liu, De-Shuang Huang

Publikováno v: PLoS Computational Biology, Vol 18, Iss 3, p e1009941 (2022)

Transcription factors (TFs) play an important role in regulating gene expression, thus the identification of the sites bound by them has become a fundamental step for molecular and cellular biology. In this paper, we developed a deep learning framewo

Externí odkaz: https://doaj.org/article/c701d34466cd47dfb1aa625af0ecf558

Zobrazit plný text záznamu

Plný text ve formátu HTML

Using Fully Convolutional Network to Locate Transcription Factor Binding Sites Based on DNA Sequence and Conservation Information

Autor: Qinhu Zhang, Youhong Xu, Siguo Wang, Yong Wu, Yuannong Ye, Chang-An Yuan, Valeriya Gribova, Vladimir Fedorovich Filaretov, De-Shuang Huang

Publikováno v: IEEE/ACM transactions on computational biology and bioinformatics.

Transcription factors (TFs) play a part in gene expression. TFs can form complex gene expression regulation system by combining with DNA. Thereby, identifying the binding regions has become an indispensable step for understanding the regulatory mecha

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::00206ccc604f9127c9dbac33f616988a
https://pubmed.ncbi.nlm.nih.gov/36374878

Zobrazit plný text záznamu

In silico prediction methods of self-interacting proteins: an empirical and academic survey

Autor: Zhanheng Chen, Zhuhong You, Qinhu Zhang, Zhenhao Guo, Siguo Wang, Yanbin Wang

Publikováno v: Frontiers of Computer Science. 17

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::20aaaf6bf3a964e44d4a5ab558e3f795
https://doi.org/10.1007/s11704-022-1563-1

Zobrazit plný text záznamu

Computational prediction and characterization of cell-type-specific and shared binding sites

Autor: Qinhu Zhang, Pengrui Teng, Siguo Wang, Ying He, Zhen Cui, Zhenghao Guo, Yixin Liu, Changan Yuan, Qi Liu, De-Shuang Huang

Publikováno v: Bioinformatics (Oxford, England). 39(1)

Motivation Cell-type-specific gene expression is maintained in large part by transcription factors (TFs) selectively binding to distinct sets of sites in different cell types. Recent research works have provided evidence that such cell-type-specific

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2d9a1bb8977b64d1f462abfe69229537
https://pubmed.ncbi.nlm.nih.gov/36484687

Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání