Track topics on Twitter Track topics that are important to you
We study the problem of computing a minimal subset of nodes of a given asynchronous Boolean network that need to be perturbed in a single-step to drive its dynamics from an initial state to a target steady state (or attractor), which we call the source-target control of Boolean networks. Due to the phenomenon of state-space explosion, a simple global approach that performs computations on the entire network, may not scale well for large networks. We believe that efficient algorithms for such networks must exploit the structure of the networks together with their dynamics. Taking this view, we derive a decomposition-based solution to the minimal source-target control problem which can be significantly faster than the existing approaches on large networks. We then show that the solution can be further optimised if we take into account appropriate information about the source state. We apply our solutions to both real-life biological networks and randomly generated networks, demonstrating the efficiency and efficacy of our approach.
This article was published in the following journal.
Name: IEEE/ACM transactions on computational biology and bioinformatics
Boolean networks are a widely used qualitative approach for modelling and analysing biological systems. However, their application is restricted by the well-known state space explosion problem which m...
Complex diseases such as Cancer or Alzheimer's are caused by multiple molecular perturbations leading to pathological cellular behavior. However, the identification of the disease-induced molecular pe...
The brain controls various cognitive functions in a robust and efficient way. What is the control architecture of brain networks that enables such robust and optimal control? Is this brain control arc...
In this brief, we investigate the robustness of outputs with respect to disturbances for Boolean control networks (BCNs) by semi-tensor product (STP) of matrices. First, BCNs are converted into the co...
Genetic regulatory networks control ontogeny. For fifty years Boolean networks have served as models of such systems, ranging from ensembles of random Boolean networks as models for generic properties...
This study evaluates the use of a social-network approach to encourage African-American men who have sex with men (AAMSM) to adopt pre-exposure prophylaxis (PrEP) to prevent HIV infection....
There are significant and persistent disparities in access to kidney transplantation and as a result most patients with end stage renal disease receive hemodialysis (HD). HD is unique as i...
This is a pilot study with a cross-sectional research design to recruit Hispanic/Latina and African American adolescent and young adult women, aged 13-24 years to serve as index recruiters...
This study evaluates whether a supported self-management approach to gout is able to achieve target levels of serum urate, and better control of gout flares.
The brain networks controlling movement are complex, involving multiple areas of the brain. Some neurological diseases, like Parkinson's disease, cause abnormalities in the brain networks....
Networks of nerve cells that control the firing patterns of MOTOR NEURONS to produce rhythmic movements such as MASTICATION; WALKING; SWIMMING; RESPIRATION; and PERISTALSIS.
An anti-CTLA-4 ANTIGEN monoclonal antibody initially indicated for the treatment of certain types of metastatic MELANOMA. Its mode of actions may include blocking of CTLA-4 mediated inhibition of CYTOTOXIC T LYMPHOCYTES, allowing for more efficient destruction of target tumor cells.
An integrated professional approach to screening, evaluation, control, and reduction of abnormal WEIGHT GAIN.
A nuclear transcription factor. Heterodimerization with RETINOID X RECEPTOR GAMMA is important to metabolism of LIPIDS. It is the target of FIBRATES to control HYPERLIPIDEMIAS.
Any situation where an animal or human is trained to respond differentially to two stimuli (e.g., approach and avoidance) under reward and punishment conditions and subsequently trained under reversed reward values (i.e., the approach which was previously rewarded is punished and vice versa).
Biological therapy involves the use of living organisms, substances derived from living organisms, or laboratory-produced versions of such substances to treat disease. Some biological therapies for cancer use vaccines or bacteria to stimulate the body&rs...