Quantitative Biology
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Perspective on the q‐bio Summer School and Conference: 2007 – 2014 and beyond
Quantitative Biology - Tập 2 Số 1 - Trang 54-58 - 2014
Generic properties of random gene regulatory networks
Quantitative Biology - Tập 1 - Trang 253-260 - 2014
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...
International Workshop on Applications of Probability and Statistics to Biology, July 11–13, 2019
Quantitative Biology - Tập 8 - Trang 177-186 - 2019
System identification and parameter estimation in mathematical medicine: examples demonstrated for prostate cancer
Quantitative Biology - - 2016
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...
Strategic planning for national biomedical big data infrastructure in China
Quantitative Biology - Tập 5 - Trang 272-275 - 2017
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...
On the possibility of identifying human subjects using behavioural complexity analyses
Quantitative Biology - Tập 4 Số 4 - Trang 261-269 - 2016
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 characterized by a
fractional dimension using non‐invasive longer‐time acquisitions of heart rate,
perfusion, b...
MRHCA: a nonparametric statistics based method for hub and co-expression module identification in large gene co-expression network
Quantitative Biology - Tập 6 - Trang 40-55 - 2018
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...
Comprehensive simulation of metagenomic sequencing data with non‐uniform sampling distribution
Quantitative Biology - Tập 6 Số 2 - Trang 175-185 - 2018
BackgroundMetagenomic sequencing is a complex sampling procedure from unknown
mixtures of many genomes. Having metagenome data with known genome compositions
is essential for both benchmarking bioinformatics software and for investigating
influences of various factors on the data. Compared to data from real microbiome
samples or from defined microbial mock community, simulated data with proper
com...
On the statistical significance of protein complex
Quantitative Biology - Tập 6 - Trang 313-320 - 2018
Statistical validation of predicted complexes is a fundamental issue in
proteomics and bioinformatics. The target is to measure the statistical
significance of each predicted complex in terms of p-values. Surprisingly, this
issue has not received much attention in the literature. To our knowledge, only
a few research efforts have been made towards this direction. In this article,
we propose a nove...
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