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Computational biology contributes important solutions for major biological challenges. Unfortunately, most applications in computational biology are highly compute-intensive and associated with extensive computing times. Biological problems of interest are often not treatable with traditional simulation models on conventional multi-core CPU systems. This interdisciplinary work introduces a new multi-timescale...
Turning non-autonomic ventricular cells into pacemaking cells is believed to hold the key for making a bio-pacemaker that could potentially treat patients with cardiac conduction diseases. In this article, we analyze the effects of various membrane ion channel currents on ventricular automaticity induced by reducing the inward-rectifier K+ current (IK1). It was found that the L-type calcium current...
This paper presents the budgeted transcript discovery problem (BTD): deciding how to spend a given research budget collecting data, using a combination of microarrays and PCRs, to discover which transcripts are differentially expressed with respect to a given phenotype. We present algorithms that address this task by sequentially analyzing the data collected so far, to decide which data would be most...
Epigenetic changes correspond to heritable modifications of the chromosome structure, which do not involve alteration of the DNA sequence but do affect gene expression. These mechanisms play an important role in normal cell differentiation, but aberration is associated also with several diseases, including cancer and neural disorders. In consequence, despite intensive studies in recent years, the...
S-system is a commonly used model for dynamic biological system. However, due to technical limitations, biological reaction networks are often only partially observable, which indicates that not all individuals incorporated in the model can be measured directly. Given a limited amount and quality of experimental data, it cannot be assured that the model structure and parameters can be estimated unambiguously...
MicroRNAs (miRNAs) are small non-coding RNAs which cause target genes degradation or translational inhibition. Constructing functional miRNAs regulatory module can be a significant step towards the discovery of their regulatory roles in various development programs. In this paper, we present a Correlated Correspondence Regulatory Module model which builds on modified Correlated Topic Model (CTM)....
Modeling and simulation of gene-regulatory networks (GRNs) has become an important aspect of modern systems biology investigations into mechanisms underlying gene regulation. An important and unsolved problem in this area is the automated inference (reverse-engineering) of dynamic, mechanistic GRN models from time-course gene expression data. The conventional one-stage model inference algorithm determines...
We develop a novel distant supervised model that integrates the results from open information extraction techniques to perform relation extraction task from biomedical literature. Unlike state-of-the-art models for relation extraction in biomedical domain which are mainly based on supervised methods, our approach does not require manually-labeled instances. In addition, our model incorporates a grouping...
Biological systems span several orders of magnitude in space and time from intracellular pathways to tissue-level processes. Many studies focus on molecular level events while other studies focus on cellular level and tissue level interactions. The immune system is highly complex and dynamic, encompassing hierarchical interactions with dimensions ranging from nanometers to meters and time scales from...
Fetal growth curves and the corresponding interpretation of biometric data represent an essential diagnostic tool in clinical practice and for epidemiological studies, but their validity is questioned by the population-reshuffling phenomenon and by other factors. To restore their diagnostic effectiveness, a suitable interpretative model has to be developed based on new parameters and on a global approach...
Currently, there are many multivariate linear regression algorithms being used for predicting the bioactive capacity of herbal formulae or herbal extracts from their chromatographic fingerprints, such as Principal Component Regression (PCR), Partial Least Squares Regression (PLSR), Orthogonal Projections to Latent Structures (OPLS) and Elastic Net (EN). In this study, the predicting performance and...
An integrated modeling platform was developed for assessing the potential release rates of ENMs and their environmental distribution. ENM release rates are estimated via life cycle assessment based approach by tracking the target ENM throughout its life cycle from production to release to the environment. Potential ENM exposure concentrations and mass distribution in the various environmental media...
Most phylogeny estimation systems such as SATe2 or DACTAL use fixed configurations and tools that make them suitable only for solving specific problems. Out of that scope, a hand-made combination of individual tools and methods has to be composed in order to get the desired phylogeny estimation. PhyloFlow is a new framework based on a workflow extendable to a wide range of tasks in phylogenetic analysis...
We propose a semi-informative aware approach using the topic model on query expansion problem in the biomedicine domain. the demographics and disease information is applied to semi-structure the topic model as the “known” label, compared to the traditional latent topics in topic modelling. Then, we suggest to select three terms from the top ranked documents to expand the query, based on the assumption...
Quantile normalization (QN) is a technique for microarray data processing and is the default normalization method in the Robust Multi-array Average (RMA) procedure, which was primarily designed for analysing gene expression data from Affymetrix arrays. Given the abundance of Affymetrix microarrays and the popularity of the RMA method, it is crucially important that the normalization procedure is applied...
Dopamine is an important neurotransmitter responsible for regulating various brain functions such as learning and cognition. Dysfunctions within the dopaminergic system are implicated in many neurological and neuropsychiatric disorders. To understand such a complex system, biologically realistic multiscale computational models are necessary. Such models require the extraction of relevant and important...
Despite extensive studies in cytogenetic and mutations in leukemia cancer, new diagnoses were detected each year. This is due to multifactorial characteristic of hematopoietic disease and a lack of systematic-level information on genetic interaction and pathways between markers to understand the development and progression of leukemia. Thus, this study aims to sought a systems biology approach to...
This paper proposes a novel survival time pathway hunting method based on gene links. In the method, we incorporate gene link information for testing how significantly a pathway is associated with cancer patient's survival. Specifically, we establish a link-based Cox proportional hazard model (Link-Cox), in which two linked genes are considered together as a link variable and the association with...
Coreference resolution recently plays a more and more important role for many natural language processing tasks. In this paper, we propose two methods for the biomedical coreference resolution. One is the single machine learning method (SVM ranker-learning algorithm) which selects appropriate features for the pronoun and noun phrase coreference resolution respectively. The other one is the hybrid...
Many scientific experiments are designed as computational workflows in bioinformatics. However, the amount of data generated increases at every phase of each execution, hindering the identification of the source and the transformation of data. Therefore, it has become necessary to create new tools to store data provenance, mainly which resources and parameters were used to generate the results, among...
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