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In protein structure, knot is a vital part. Structures that contain a knot formed by the path of the polypeptide backbone represent some of the most complex topologies observed in proteins. Detecting these knots, we hope to find out some information or chances to cope with protein malfunction or abnormalities. There are some state of the art algorithms to find knot in a protein structure e.g. KNOT...
Primary sequence motif extraction from protein amino sequences is a field of growing importance in bioinformatics due to its relevance to both sequential and structural analysis. Many approaches for motif extraction include two limitations: a reliance on discovering an existing, known protein homologue to perform motif extraction or structural analysis, and an assumed motif length. This work would...
Most proteins express their functions by binding with other proteins or molecular compounds called ligands. The local portion involved in binding is called a binding site. The characteristics of the binding site often determine the function of the protein, so clarifying the location of the binding site of the protein helps analyze the function of proteins. Binding sites that bind to similar ligands...
Transcriptional regulatory network identification is both a fundamental challenge in systems biology and an important practical application of data mining and machine learning. In this study, we propose a semi-supervised learning-based integrative scoring approach to tackle this challenge and predict transcriptional regulations. Our approach out-performs a state-of-the-art label propagation method...
The mathematical model described in this paper is based on a discovery of a phenomenon related to red blood cells. In this phenomenon, the hemolysate of red blood cells reacts with antibodies from the plasma of the same patient. Using proteomics approach to identify those hemolysate antigens and then build a database containing those antigens can help in diagnosis, prognosis, and treatment of disease...
We consider the problem of similarity search in applications where the cost of computing the similarity between two records is very expensive, and the similarity measure is not a metric. In such applications, comparing even a tiny fraction of the database records to a single query record can be orders of magnitude slower than reading the entire database from disk, and indexing is often not possible...
Previous studies have suggested that some graph properties of protein interaction networks might be related with gene morbidity. In particular, it has been suggested that when a polymorphism affects a gene, it is more likely to produce a disease if the node degree in the interaction network is higher than for other genes. However, these results do not take into account the possible bias introduced...
Molecular motors can be considered as biological molecular devices that are indispensable agents or machines for movement in living organisms. The most common motor proteins are Myosin, Kinesin and Dynein which are responsible for nanoscale cellular and molecular movement. In this work, the above mentioned protein molecules have been subjected to structural and sequence analysis, modeling and molecular...
Bi- or even multistable behavior is a recurrent phenomenon in gene regulation networks. These networks have the capacity to operate in two or more distinct modes in a stable manner. In this work, we consider gene regulation networks with known interaction structure but unknown reaction kinetics. Additionally, it is assumed that several distinct operation modes were observed experimentally whereby...
In this paper we describe a new maximum likelihood approach to infer kinetic rate constants from time-course data and apply it to estimate the rate constants of the synthesis and degradation of the mRNA of Cdc20 protein, and the rate constant of the transcription of the cdc20 gene into Cdc20 protein. The Cdc20 protein plays a crucial role in eukaryotic cell cycle, as it codes for the cyclin antagonist...
Software for computational analysis and simulation of biochemical systems has become one of the major computational tools in systems biology in recent years. Most of them use parameterized differential equations to model and describe biochemical systems. Although biochemical principles, such as enzyme mechanics, have been developed to derive kinetic rate equations, measuring and providing parameters...
This paper presents a numerical solution to describe growth factor-receptor binding under flow through hollow fibers of a bioreactor. The multi-physics of fluid flow, the kinetics of fibroblast growth factor (FGF-2) binding to its receptor (FGFR) and heparan sulfate proteoglycan (HSPG) and FGF-2 mass transport is modeled by a set of coupled nonlinear partial differential equations (PDEs) and coupled...
We show that multiple structure alignment (MStA) using contact maps is equivalent to the problem of finding a sample mean of contact maps. From this result, we derive a subgradient method for solving the MStA method. Experiments show that the proposed algorithm is a flexible alignment method that provides an excellent tradeoff between accuracy and speed.
There has been a great deal of recent interest in identifying functional modules from protein interaction and gene expression data. One commonly used computational technique is simulated annealing, which while asymptotically correct frequently suffers from slow convergence. In this paper we outline and exploit the analogy between finding functional modules and finding Haplotype Blocks from genetic...
To evaluate cytokine network of pulmonary fibrosis. A systematic literature search of EMBASE, MEDLINE, Cochrane Library was conducted through December 2007. Then potential regulatory pathway of cytokines was analyzed with a cubic spline intepolation and a linear differential model. The cytokines of silicosis fibrosis tissue were identified by meta-analysis. The related cytokines participated pulmonary...
The aim of this study is based on GM(0,N) model to evaluate the biochemical factors in preterm neonates, include growth hormone (GH), insulin-like growth factors (IGFs), IGF-binding proteins (IGFBPs) and leptin, the proteins known to be involved in the regulation of growth. And find the influence for each factor corresponding with the body mass index(BMI) and postnatal growth(PI). First, we use the...
Heat shock protein, denoted by HSP throughout this paper for the simplicity, is one of the families of proteins which plays an important role to keep the normal activity of a cell. Actually, when a cell is given a stress by heat, metal ion, alcohol and so on, HSP is synthesized a lot to keep the life of a cell from such stress. In this paper, we pay attention to the biochemical reaction of HSP synthesis...
This paper is concerned with validating a mathematical model of regulation in the tryptophan operon using global optimization. Although a number of models for this biochemical network are proposed, in many cases only qualitative agreement between the model output and experimental data was demonstrated, since very little information is currently available to guide the selection of parameter values...
A fundamental problem in systems biology consists of determining the equilibrium points of genetic regulatory networks, since the knowledge of these points is often required in order to investigate important properties such as stability. Unfortunately, this problem amounts to computing the solutions of a system of nonlinear equations, and it is well known that this is a difficult problem as no existing...
In this paper, we present RBNBC, a repeat based Naive Bayes classifier of bio-sequences that uses maximal frequent subsequences as features. RBNBC's design is based on generic ideas that can apply to other domains where the data is organized as collections of sequences. Specifically, RBNBC uses a novel formulation of Naive Bayes that incorporates repeated occurrences of subsequences within each sequence...
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