Transcriptome-wide association studies: a view from Mendelian randomizationQuantitative Biology - - Trang 1-15 - 2020
Huanhuan Zhu, Xiang Zhou
Genome-wide association studies (GWASs) have identified thousands of genetic variants that are associated with many complex traits. However, their biological mechanisms remain largely unknown. Transcriptome-wide association studies (TWAS) have been recently proposed as an invaluable tool for investigating the potential gene regulatory mechanisms underlying variant-trait associations. Specifically,...... hiện toàn bộ
Generic properties of random gene regulatory networksQuantitative Biology - Tập 1 - Trang 253-260 - 2014
Zhiyuan Li, Simone Bianco, Zhaoyang Zhang, Chao Tang
Modeling gene regulatory networks (GRNs) is an important topic in systems biology. Although there has been much work focusing on various specific systems, the generic behavior of GRNs with continuous variables is still elusive. In particular, it is not clear typically how attractors partition among the three types of orbits: steady state, periodic and chaotic, and how the dynamical properties chan...... hiện toàn bộ
System identification and parameter estimation in mathematical medicine: examples demonstrated for prostate cancerQuantitative Biology - - 2016
Yoshito Hirata, Kai Morino, Taiji Suzuki, Qian Guo, Hiroshi Fukuhara, Kazuyuki Aihara
We review our studies on how to identify the most appropriate models of diseases, and how to determine their parameters in a quantitative manner given a short time series of biomarkers, using intermittent androgen deprivation therapy of prostate cancer as an example. Recently, it has become possible to estimate the specific parameters of individual patients within a reasonable time by employing th...... hiện toàn bộ
Synthetic biology: a new approach to study biological pattern formationQuantitative Biology - Tập 1 - Trang 246-252 - 2014
Chenli Liu, Xiongfei Fu, Jian-Dong Huang
The principles and molecular mechanisms underlying biological pattern formation are difficult to elucidate in most cases due to the overwhelming physiologic complexity associated with the natural context. The understanding of a particular mechanism, not to speak of underlying universal principles, is difficult due to the diversity and uncertainty of the biological systems. Although current genetic...... hiện toàn bộ
Strategic planning for national biomedical big data infrastructure in ChinaQuantitative Biology - Tập 5 - Trang 272-275 - 2017
Zhen Wang, Zefeng Wang, Yixue Li
The promise that big data will revolutionize scientific discovery and technology innovation is now being widely recognized. With the explosive growth of biomedical data, life science is being transformed into a digital science in which novel insights are gained from in-depth data analysis and modeling. Extensive and innovative utilization of biomedical big data is a key to the success of precision...... hiện toàn bộ
On the possibility of identifying human subjects using behavioural complexity analysesQuantitative Biology - Tập 4 Số 4 - Trang 261-269 - 2016
Petr Klouček, Armin von Gunten
BackgroundIdentification of human subjects using a geometric approach to complexity analysis of behavioural data is designed to provide a basis for a more precise diagnosis leading towards personalised medicine.MethodsThe approach is based on capturing behavioural time‐series that can be chara...... hiện toàn bộ
MRHCA: a nonparametric statistics based method for hub and co-expression module identification in large gene co-expression networkQuantitative Biology - Tập 6 - Trang 40-55 - 2018
Yu Zhang, Sha Cao, Jing Zhao, Burair Alsaihati, Qin Ma, Chi Zhang
Gene co-expression and differential co-expression analysis has been increasingly used to study cofunctional and co-regulatory biological mechanisms from large scale transcriptomics data sets. In this study, we develop a nonparametric approach to identify hub genes and modules in a large coexpression network with low computational and memory cost, namely MRHCA. We have applied the method to simulat...... hiện toàn bộ