Discovery of significant pathways in breast cancer metastasis via module extraction and comparison
Discovering significant pathways rather than single genes or small gene sets involved in metastasis is becoming more and more important in the study of breast cancer. Many researches have shed light on this problem. However, most of the existing works are relying on some priori biological information, which may bring bias to the models. The authors propose a new method that detects metastasis-related pathways by identifying and comparing modules in metastasis and non-metastasis gene coexpression networks. The gene co-expression networks are built by Pearson correlation coefficients, and then the modules inferred in these t...
Source: IET Systems Biology - April 1, 2014 Category: Biology Source Type: research
Degree-adjusted algorithm for prioritisation of candidate disease genes from gene expression and protein interactome
This study suggests the importance of statistically adjusting the degree distribution bias in the background network for network-based modelling of complex diseases. (Source: IET Systems Biology)
Source: IET Systems Biology - April 1, 2014 Category: Biology Source Type: research
Inferring non-synonymous single-nucleotide polymorphisms-disease associations via integration of multiple similarity networks
Detecting associations between human genetic variants and their phenotypic effects is a significant problem in understanding genetic bases of human-inherited diseases. The focus is on a typical type of genetic variants called nonsynonymous single nucleotide polymorphisms (nsSNPs), whose occurrence may potentially alter the structures of proteins, affecting functions of proteins, and thereby causing diseases. Most of the existing methods predict associations between nsSNPs and diseases based on features derived from only protein sequence and/or structure information, and give no information about which specific disease an n...
Source: IET Systems Biology - April 1, 2014 Category: Biology Source Type: research
Comprehensive study of tumour single nucleotide polymorphism array data reveals significant driver aberrations and disrupted signalling pathways in human hepatocellular cancer
The authors describe an integrated method for analysing cancer driver aberrations and disrupted pathways by using tumour single nucleotide polymorphism (SNP) arrays. The authors new method adopts a novel statistical model to explicitly quantify the SNP signals, and therefore infers the genomic aberrations, including copy number alteration and loss of heterozygosity. Examination on the dilution series dataset shows that this method can correctly identify the genomic aberrations even with the existence of severe normal cell contamination in tumour sample. Furthermore, with the results of the aberration identification obtaine...
Source: IET Systems Biology - April 1, 2014 Category: Biology Source Type: research
Editorial - Part 1: Network biology in translational bioinformatics and systems biology
Identifying driver mutations as well as disease genes that are responsible for various disorders is the key to understand the molecular mechanisms underlying diseases in translational bioinformatics. At the same time, the knowledge about drug targets can help design compounds with better efficacy. Recently, the availability of various types of molecular networks makes it possible to identify disease genes or drug targets from systematic perspectives. In this special issue, we reported the recent progress on computational approaches that have been developed to predict disease genes and drug targets. (Source: IET Systems Biology)
Source: IET Systems Biology - April 1, 2014 Category: Biology Source Type: research
Erratum
(Source: IET Systems Biology)
Source: IET Systems Biology - February 1, 2014 Category: Biology Source Type: research
On the design of human immunodeficiency virus treatment based on a non-linear time-delay model
In this study, using a non-linear time-delay model, the authors design some suboptimal highly active antiretroviral therapy (HAART) [http://www.en.wikipedia.org/wiki/Protease_inhibitor_%28pharmacology%29] regimens for patients with HIV. The non-linear delayed model is used to describe the dynamical interactions between HIV and human immune system in the presence of HAART. Based on the model, a set point tracking problem is defined in order to set the number of susceptible CD4+T cells to a desired value. To solve this set point tracking problem in a suboptimal way, the authors introduce a new method which is able to conside...
Source: IET Systems Biology - February 1, 2014 Category: Biology Source Type: research
Synthesising periodic triggering signals with genetic oscillators
The potential of the clock lies in its role of triggering logic reaction for sequential biological circuits. This research introduces an idea of designing a genetic clock generator by Fourier series based on the genetic oscillators. The authors generalise the design idea using a combination of fundamental sinusoidal signals. Since biochemical reaction of the biological system is extremely slow, however, transition between minimal and maximal levels is instantaneous for an ideal clock signal; it is thus not directly realisable in biological systems. That means it would be hard to directly synthesize a square wave generator ...
Source: IET Systems Biology - February 1, 2014 Category: Biology Source Type: research
Systems analysis utilising pathway interactions identifies sonic hedgehog pathway as a primary biomarker and oncogenic target in hepatocellular carcinoma
The development and progression of cancer is associated with disruption of biological networks. Historically studies have identified sets of signature genes involved in events ultimately leading to the development of cancer. Identification of such sets does not indicate which biologic processes are oncogenic drivers and makes it difficult to identify key networks to target for interventions. Using a comprehensive, integrated computational approach, the authors identify the sonic hedgehog (SHH) pathway as the gene network that most significantly distinguishes tumour and tumour-adjacent samples in human hepatocellular carcin...
Source: IET Systems Biology - December 1, 2013 Category: Biology Source Type: research
Evaluating treatment of osteoporosis using particle swarm on a bone remodelling mathematical model
In this study, the authors built a mathematical model of bone remodelling and developed a treatment strategy for mechanical loading and salubrinal, a synthetic chemical agent that enhances bone formation and prevents bone resorption. The model formulated a temporal BMD change of a mouse's whole skeleton in response to ovariectomy, mechanical loading and administration of salubrinal. Particle swarm optimisation was employed to maximise a performance index (a function of BMD and treatment cost) to find an ideal sequence of treatment. The best treatment was found to start with mechanical loading followed by salubrinal. As tre...
Source: IET Systems Biology - December 1, 2013 Category: Biology Source Type: research
Clustering based on multiple biological information: approach for predicting protein complexes
Protein complexes are a cornerstone of many biological processes. Protein-protein interaction (PPI) data enable a number of computational methods for predicting protein complexes. However, the insufficiency of the PPI data significantly lowers the accuracy of computational methods. In the current work, the authors develop a novel method named clustering based on multiple biological information (CMBI) to discover protein complexes via the integration of multiple biological resources including gene expression profiles, essential protein information and PPI data. First, CMBI defines the functional similarity of each pair of i...
Source: IET Systems Biology - October 1, 2013 Category: Biology Source Type: research
M-matrix-based stability conditions for genetic regulatory networks with time-varying delays and noise perturbations
Stability is essential for designing and controlling any dynamic systems. Recently, the stability of genetic regulatory networks has been widely studied by employing linear matrix inequality (LMI) approach, which results in checking the existence of feasible solutions to high-dimensional LMIs. In the previous study, the authors present several stability conditions for genetic regulatory networks with time-varying delays, based on M-matrix theory and using the non-smooth Lyapunov function, which results in determining whether a low-dimensional matrix is a nonsingular M-matrix. However, the previous approach cannot be applie...
Source: IET Systems Biology - October 1, 2013 Category: Biology Source Type: research
Analysis and simulation of an adefovir anti-hepatitis b virus infection therapy immune model with alanine aminotransferase
This study describes one anti- HBV therapy immune model with alanine aminotransferase (ALT) based on standard mass action incidences. There are two basic infection reproductive numbers R0 and R1 in the model. It is proved that if R0 < 1 and R0 < 1, the disease free equilibrium is locally and globally asymptotically stable, respectively. For the endemic equilibrium, simulation shows that if R1 > 1, it may be also globally asymptotically stable. Simulations based on clinical data of HBV DNA and ALT can explain some clinical phenomena. Simulations of the correlation between liver cells, HBV DNA, cytotoxic T lymphocytes and AL...
Source: IET Systems Biology - October 1, 2013 Category: Biology Source Type: research
Gene regulatory network discovery using pairwise granger causality
In this study, the authors first investigate with synthetic data how spurious causalities (false discoveries) may arise because of the use of pairwise rather than full-model GC detection. Furthermore, spurious causalities may also arise if the order of the vector autoregressive model is not high enough. As a remedy, the authors demonstrate that model validation techniques can effectively reduce the number of false discoveries. Then, they apply pairwise GC with model validation to the real human HeLa cell-cycle dataset. They find that Akaike information criterion is generally most suitable for determining model order, but p...
Source: IET Systems Biology - October 1, 2013 Category: Biology Source Type: research
Drug repositioning framework by incorporating functional information
As a shortcut for drug development, drug repositioning draws more and more attention in pharmaceutical industry to identify new indications for marketed drugs or drugs failed in late clinical trial phase. At the same time, the abundant highthroughput data pushes the computationally repositioning drugs a hot topic in the area of systems biology. Here, the authors propose a general framework for repositioning drug by incorporating various functional information. The framework starts with the identification of differentially expressed gene sets under disease state and drug treatment. Then the disease and drug are associated b...
Source: IET Systems Biology - October 1, 2013 Category: Biology Source Type: research
