Inference on the structure of gene regulatory networks

被引:8
作者
Wang, Yue [1 ,2 ]
Wang, Zikun [3 ]
机构
[1] Univ Calif Los Angeles, Dept Computat Med, Los Angeles, CA 90095 USA
[2] Inst Hautes Etud Sci, F-91440 Bures Sur Yvette, Essonne, France
[3] Rockefeller Univ, Lab Genet, New York, NY 10065 USA
关键词
Inference; Gene regulatory network; Independence; Differential equation; RNA-SEQ; EXPRESSION; MECHANISMS;
D O I
10.1016/j.jtbi.2022.111055
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
In this paper, we conduct theoretical analyses on inferring the structure of gene regulatory networks. Depending on the experimental method and data type, the inference problem is classified into 20 different scenarios. For each scenario, we discuss the problem that with enough data, under what assumptions, what can be inferred about the structure. For scenarios that have been covered in the literature, we provide a brief review. For scenarios that have not been covered in literature, if the structure can be inferred, we propose new mathematical inference methods and evaluate them on simulated data. Otherwise, we prove that the structure cannot be inferred. (c) 2022 Elsevier Ltd. All rights reserved.
引用
收藏
页数:18
相关论文
共 67 条
[1]   Identifying cell populations with scRNASeq [J].
Andrews, Tallulah S. ;
Hemberg, Martin .
MOLECULAR ASPECTS OF MEDICINE, 2018, 59 :114-122
[2]  
[Anonymous], 2001, Mathematical Biology II: Spatial Models and Biomedical Applications
[3]   Inference of gene regulatory networks and compound mode of action from time course gene expression profiles [J].
Bansal, M ;
Della Gatta, G ;
di Bernardo, D .
BIOINFORMATICS, 2006, 22 (07) :815-822
[4]   Granger Causality and Transfer Entropy Are Equivalent for Gaussian Variables [J].
Barnett, Lionel ;
Barrett, Adam B. ;
Seth, Anil K. .
PHYSICAL REVIEW LETTERS, 2009, 103 (23)
[5]   A QUALITATIVE-ANALYSIS OF X = AX + B [J].
BONE, T ;
JEFFRIES, C ;
KLEE, V .
DISCRETE APPLIED MATHEMATICS, 1988, 20 (01) :9-30
[6]   Using Aggregated Relational Data to Feasibly Identify Network Structure without Network Data [J].
Breza, Emily ;
Chandrasekhar, Arun G. ;
McCormick, Tyler H. ;
Pan, Mengjie .
AMERICAN ECONOMIC REVIEW, 2020, 110 (08) :2454-2484
[7]   Network Structure Inference, A Survey: Motivations, Methods, and Applications [J].
Brugere, Ivan ;
Gallagher, Brian ;
Berger-Wolf, Tanya Y. .
ACM COMPUTING SURVEYS, 2018, 51 (02)
[8]   A human cell atlas of fetal gene expression [J].
Cao, Junyue ;
O'Day, Diana R. ;
Pliner, Hannah A. ;
Kingsley, Paul D. ;
Deng, Mei ;
Daza, Riza M. ;
Zager, Michael A. ;
Aldinger, Kimberly A. ;
Blecher-Gonen, Ronnie ;
Zhang, Fan ;
Spielmann, Malte ;
Palis, James ;
Doherty, Dan ;
Steemers, Frank J. ;
Glass, Ian A. ;
Trapnell, Cole ;
Shendure, Jay .
SCIENCE, 2020, 370 (6518) :808-+
[9]  
Casella G., 2021, STAT INFERENCE
[10]   Mechanisms of retinoic acid signalling and its roles in organ and limb development [J].
Cunningham, Thomas J. ;
Duester, Gregg .
NATURE REVIEWS MOLECULAR CELL BIOLOGY, 2015, 16 (02) :110-123