Literature DB >> 31091308

Transcription factors-DNA interactions in rice: identification and verification.

Zijie Shen1, Yuan Lin2, Quan Zou1,3.   

Abstract

The completion of the rice genome sequence paved the way for rice functional genomics research. Additionally, the functional characterization of transcription factors is currently a popular and crucial objective among researchers. Transcription factors are one of the groups of proteins that bind to either enhancer or promoter regions of genes to regulate expression. On the basis of several typical examples of transcription factor analyses, we herein summarize selected research strategies and methods and introduce their advantages and disadvantages. This review may provide some theoretical and technical guidelines for future investigations of transcription factors, which may be helpful to develop new rice varieties with ideal traits.
© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  DNA–protein interactions; functional genomics; methylated DNA–TF interactions; transcription factors

Year:  2020        PMID: 31091308     DOI: 10.1093/bib/bbz045

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  5 in total

1.  iCDA-CMG: identifying circRNA-disease associations by federating multi-similarity fusion and collective matrix completion.

Authors:  Qiu Xiao; Jiancheng Zhong; Xiwei Tang; Jiawei Luo
Journal:  Mol Genet Genomics       Date:  2020-11-06       Impact factor: 3.291

2.  Critical assessment of computational tools for prokaryotic and eukaryotic promoter prediction.

Authors:  Meng Zhang; Cangzhi Jia; Fuyi Li; Chen Li; Yan Zhu; Tatsuya Akutsu; Geoffrey I Webb; Quan Zou; Lachlan J M Coin; Jiangning Song
Journal:  Brief Bioinform       Date:  2022-03-10       Impact factor: 11.622

3.  MAResNet: predicting transcription factor binding sites by combining multi-scale bottom-up and top-down attention and residual network.

Authors:  Ke Han; Long-Chen Shen; Yi-Heng Zhu; Jian Xu; Jiangning Song; Dong-Jun Yu
Journal:  Brief Bioinform       Date:  2022-01-17       Impact factor: 13.994

4.  MILNP: Plant lncRNA-miRNA Interaction Prediction Based on Improved Linear Neighborhood Similarity and Label Propagation.

Authors:  Lijun Cai; Mingyu Gao; Xuanbai Ren; Xiangzheng Fu; Junlin Xu; Peng Wang; Yifan Chen
Journal:  Front Plant Sci       Date:  2022-03-25       Impact factor: 5.753

5.  Genome-Wide Identification, Transcript Profiling and Bioinformatic Analyses of GRAS Transcription Factor Genes in Rice.

Authors:  Mouboni Dutta; Anusree Saha; Mazahar Moin; Pulugurtha Bharadwaja Kirti
Journal:  Front Plant Sci       Date:  2021-11-26       Impact factor: 5.753

  5 in total

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