NARROMI: a noise and redundancy reduction technique improves accuracy of gene regulatory network inference

Xiujun ZhangLuonan Chen


Reconstruction of gene regulatory networks (GRNs) is of utmost interest to biologists and is vital for understanding the complex regulatory mechanisms within the cell. Despite various methods developed for reconstruction of GRNs from gene expression profiles, they are notorious for high false positive rate owing to the noise inherited in the data, especially for the dataset with a large number of genes but a small number of samples. In this work, we present a novel method, namely NARROMI, to improve the accuracy of GRN inference by combining ordinary differential equation-based recursive optimization (RO) and information theory-based mutual information (MI). In the proposed algorithm, the noisy regulations with low pairwise correlations are first removed by using MI, and the redundant regulations from indirect regulators are further excluded by RO to improve the accuracy of inferred GRNs. In particular, the RO step can help to determine regulatory directions without prior knowledge of regulators. The results on benchmark datasets from Dialogue for Reverse Engineering Assessments and Methods challenge and experimentally determined GRN of Escherichia coli show that NARROMI significantly outperforms other popular methods in terms ...Continue Reading


Aug 10, 2000·Cell·T R HughesS H Friend
May 2, 2002·Proceedings of the National Academy of Sciences of the United States of America·M K Stephen YeungJames J Collins
Dec 16, 2003·Proceedings of the National Academy of Sciences of the United States of America·James C LiaoVwani P Roychowdhury
Jul 31, 2004·Bioinformatics·Alberto de la FuentePedro Mendes
Mar 15, 2005·Nature Biotechnology·Diego di BernardoJames J Collins
Mar 22, 2005·Nature Genetics·Katia BassoAndrea Califano
May 17, 2006·Proceedings of the National Academy of Sciences of the United States of America·Ning SunHongyu Zhao
Jul 26, 2006·Bioinformatics·Yong WangLuonan Chen
Feb 15, 2007·Molecular Systems Biology·Mukesh BansalDiego di Bernardo
Apr 5, 2007·Nature Protocols·Hermann Schägger
Apr 5, 2007·Nature Protocols·Adam A MargolinAndrea Califano
Jul 25, 2007·Bioinformatics·Florian MarkowetzRainer Spang
Feb 1, 2008·Physical Review Letters·Stefan Frenzel, Bernd Pompe
Jun 26, 2009·BMC Bioinformatics·Marcello CastellanoGianfranco Tarricone
Aug 28, 2009·PloS One·Scott ChristleyXiaohui Xie
Mar 24, 2010·Proceedings of the National Academy of Sciences of the United States of America·Daniel MarbachGustavo Stolovitzky
Apr 14, 2010·Proceedings of the National Academy of Sciences of the United States of America·Antti HonkelaMagnus Rattray
Sep 2, 2010·Nature Reviews. Microbiology·Riet De Smet, Kathleen Marchal
Oct 12, 2010·PloS One·Vân Anh Huynh-ThuPierre Geurts
Dec 15, 2010·Journal of Chemical Information and Modeling·Shigeru SaitoKatsuhisa Horimoto
Feb 18, 2011·Genome Research·Lesley T Macneil, Albertha J M Walhout
Aug 31, 2011·Proceedings of the National Academy of Sciences of the United States of America·Sheetal R ModiJames J Collins
Nov 16, 2011·Proceedings of the National Academy of Sciences of the United States of America·Ka Yee YeungAdrian E Raftery
Dec 17, 2011·Science·David N ReshefPardis C Sabeti
Mar 3, 2012·PLoS Computational Biology·Santiago TreviñoKevin E Bassler
Apr 3, 2012·Bioinformatics·Robert KüffnerRalf Zimmer
Jul 17, 2012·Nature Methods·Daniel MarbachGustavo Stolovitzky


Oct 24, 2013·BMC Systems Biology·Janusz Sławek, Tomasz Arodź
Nov 2, 2013·Bioinformatics·Xiangtian YuLuonan Chen
Jun 17, 2014·Journal of Theoretical Biology·Wanwei ZhangLuonan Chen
Aug 19, 2015·Computational Biology and Chemistry·Faridah Hani Mohamed SallehMohd Firdaus-Raih
Oct 10, 2015·IEEE/ACM Transactions on Computational Biology and Bioinformatics·Jeong-Rae KimKwang-Hyun Cho
Feb 18, 2016·IEEE/ACM Transactions on Computational Biology and Bioinformatics·Lin ZhuDe-Shuang Huang
Apr 12, 2016·Frontiers in Microbiology·Sylvie SchulzeJörg Linde
Sep 27, 2013·IET Systems Biology·Zikai WuLuonan Chen
Apr 6, 2016·IEEE/ACM Transactions on Computational Biology and Bioinformatics·Nitin Singh, Mathukumalli Vidyasagar
Jun 17, 2014·Journal of Theoretical Biology·Guimin Qin, Xing-Ming Zhao
Jan 28, 2014·Genomics & Informatics·Donghyeon YuTae Hyun Hwang
Aug 16, 2016·Methods : a Companion to Methods in Enzymology·Junbai WangTianhai Tian
Sep 7, 2016·Nucleic Acids Research·Xiaoping LiuLuonan Chen
Oct 8, 2016·Journal of Bioinformatics and Computational Biology·Jinwoo ParkSun Kim
Aug 2, 2016·PLoS Computational Biology·Fei LiuLuonan Chen
Apr 25, 2017·PLoS Computational Biology·Xiuli ChenJoseph M Galea
Nov 11, 2017·IET Systems Biology·Ming ShiHong-Qiang Wang
Apr 4, 2017·IEEE/ACM Transactions on Computational Biology and Bioinformatics·Aurelie PirayreJean-Christophe Pesquet
Jul 13, 2018·PloS One·Jamshid Pirgazi, Ali Reza Khanteymoori
Feb 23, 2018·Scientific Reports·Vân Anh Huynh-Thu, Pierre Geurts
Feb 6, 2020·Journal of Bioinformatics and Computational Biology·Huiqing WangChunlin Dong
Nov 22, 2018·BMC Systems Biology·Marc LegeayBéatrice Duval
Oct 18, 2018·International Journal of Molecular Sciences·Bin YangDe-Shuang Huang
Nov 26, 2018·IET Systems Biology·Wei ZhangNing Wang
Jul 22, 2020·BMC Bioinformatics·Seyed Amir MalekpourMehdi Sadeghi
Mar 3, 2017·Advances in Bioinformatics·Faridah Hani Mohamed SallehShereena M Arif
Jul 11, 2019·Journal of Bioinformatics and Computational Biology·Jamshid PirgaziMaryam Jalilkhani

Related Concepts

Alkalescens-Dispar Group
Gene Modules
Gene Expression Profiles
Escherichia coli
Gene Expression
Biologist (General)
Frontotemporal Dementia
Reconstructive Surgical Procedures

Trending Feeds


Coronaviruses encompass a large family of viruses that cause the common cold as well as more serious diseases, such as the ongoing outbreak of coronavirus disease 2019 (COVID-19; formally known as 2019-nCoV). Coronaviruses can spread from animals to humans; symptoms include fever, cough, shortness of breath, and breathing difficulties; in more severe cases, infection can lead to death. This feed covers recent research on COVID-19.

Synthetic Genetic Array Analysis

Synthetic genetic arrays allow the systematic examination of genetic interactions. Here is the latest research focusing on synthetic genetic arrays and their analyses.

Neural Activity: Imaging

Imaging of neural activity in vivo has developed rapidly recently with the advancement of fluorescence microscopy, including new applications using miniaturized microscopes (miniscopes). This feed follows the progress in this growing field.

Computational Methods for Protein Structures

Computational methods employing machine learning algorithms are powerful tools that can be used to predict the effect of mutations on protein structure. This is important in neurodegenerative disorders, where some mutations can cause the formation of toxic protein aggregations. This feed follows the latests insights into the relationships between mutation and protein structure leading to better understanding of disease.

Congenital Hyperinsulinism

Congenital hyperinsulinism is caused by genetic mutations resulting in excess insulin secretion from beta cells of the pancreas. Here is the latest research.

Chronic Fatigue Syndrome

Chronic fatigue syndrome is a disease characterized by unexplained disabling fatigue; the pathology of which is incompletely understood. Discover the latest research on chronic fatigue syndrome here.

Epigenetic Memory

Epigenetic memory refers to the heritable genetic changes that are not explained by the DNA sequence. Find the latest research on epigenetic memory here.

Cell Atlas of the Human Eye

Constructing a cell atlas of the human eye will require transcriptomic and histologic analysis over the lifespan. This understanding will aid in the study of development and disease. Find the latest research pertaining to the Cell Atlas of the Human Eye here.

Femoral Neoplasms

Femoral Neoplasms are bone tumors that arise in the femur. Discover the latest research on femoral neoplasms here.