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In Silico Biology

Christoph Leberecht, Florian Heinke, Dirk Labudde
A variety of mathematical models is used to describe and simulate the multitude of natural processes examined in life sciences. In this paper we present a scalable and adjustable foundation for the simulation of natural systems. Based on neighborhood relations in graphs and the complex interactions in cellular automata, the model uses recurrence relations to simulate changes on a mesoscopic scale. This implicit definition allows for the manipulation of every aspect of the model even during simulation. The definition of value rules ω facilitates the accumulation of change during time steps...
April 29, 2017: In Silico Biology
Necmettin Yildirim, Mehmet Emin Aktas, Seyma Nur Ozcan, Esra Akbas, Ahmet Ay
Cells maintain cellular homeostasis employing different regulatory mechanisms to respond external stimuli. We study two groups of signal-dependent transcriptional regulatory mechanisms. In the first group, we assume that repressor and activator proteins compete for binding to the same regulatory site on DNA (competitive mechanisms). In the second group, they can bind to different regulatory regions in a noncompetitive fashion (noncompetitive mechanisms). For both competitive and noncompetitive mechanisms, we studied the gene expression dynamics by increasing the repressor or decreasing the activator abundance (inhibition mechanisms), or by decreasing the repressor or increasing the activator abundance (activation mechanisms)...
August 2, 2016: In Silico Biology
J J Vaca-González, M L Gutiérrez, J M Guevara, D A Garzón-Alvarado
Articular cartilage is characterized by low cell density of only one cell type, chondrocytes, and has limited self-healing properties. When articular cartilage is affected by traumatic injuries, a therapeutic strategy such as autologous chondrocyte implantation is usually proposed for its treatment. This approach requires in vitro chondrocyte expansion to yield high cell number for cell transplantation. To improve the efficiency of this procedure, it is necessary to assess cell dynamics such as migration, proliferation and cell death during culture...
January 7, 2016: In Silico Biology
C G Zamora-Chimal, E S Zeron
We develop an exact and flexible mathematical model for Lutz and Bujard's controllable promoters. It can be used as a building block for modeling genetic systems based on them. Special attention is paid to deduce all the model parameters from reported (in vitro) experimental data. We validate our model by comparing the regulatory ranges measured in vivo by Lutz and Bujard against the ranges predicted by the model, and which are calculated as the reporter activity obtained under inducing conditions divided by the activity measured under maximal repression...
2015: In Silico Biology
Brian P Ingalls, Eric Bembenek
Analysis of metabolic networks typically begins with construction of the stoichiometry matrix, which characterizes the network topology. This matrix provides, via the balance equation, a description of the potential steady-state flow distribution. This paper begins with the observation that the balance equation depends only on the structure of linear redundancies in the network, and so can be stated in a succinct manner, leading to computational efficiencies in steady-state analysis. This alternative description of steady-state behaviour is then used to provide a novel method for network reduction, which complements existing algorithms for describing intracellular networks in terms of input-output macro-reactions (to facilitate bioprocess optimization and control)...
2015: In Silico Biology
Michael C Mackey, Moisés Santillán, Marta Tyran-Kamińska, Eduardo S Zeron
In this review, we survey work that has been carried out in the attempts of biomathematicians to understand the dynamic behaviour of simple bacterial operons starting with the initial work of the 1960's. We concentrate on the simplest of situations, discussing both repressible and inducible systems and then turning to concrete examples related to the biology of the lactose and tryptophan operons. We conclude with a brief discussion of the role of both extrinsic noise and so-called intrinsic noise in the form of translational and/or transcriptional bursting...
2015: In Silico Biology
Abhishekh Gupta, Jason Lloyd-Price, Andre S Ribeiro
Recent evidence suggests that cells employ functionally asymmetric partitioning schemes in division to cope with aging. We explore various schemes in silico, with a stochastic model of Escherichia coli that includes gene expression, non-functional proteins generation, aggregation and polar retention, and molecule partitioning in division. The model is implemented in SGNS2, which allows stochastic, multi-delayed reactions within hierarchical, transient, interlinked compartments. After setting parameter values of non-functional proteins' generation and effects that reproduce realistic intracellular and population dynamics, we investigate how the spatial organization of non-functional proteins affects mean division times of cell populations in lineages and, thus, mean cell numbers over time...
2015: In Silico Biology
Dennis Bray
Are we close to a complete inventory of living processes so that we might expect in the near future to reproduce every essential aspect necessary for life? Or are there mechanisms and processes in cells and organisms that are presently inaccessible to us? Here I argue that a close examination of a particularly well-understood system--that of Escherichia coli chemotaxis--shows we are still a long way from a complete description. There is a level of molecular uncertainty, particularly that responsible for fine-tuning and adaptation to myriad external conditions, which we presently cannot resolve or reproduce on a computer...
2015: In Silico Biology
Serghei Mangul, Adrian Caciula, Olga Glebova, Ion Mandoiu, Alex Zelikovsky
The paper addresses the problem of how to use RNA-Seq data for transcriptome reconstruction and quantification, as well as novel transcript discovery in partially annotated genomes. We present a novel annotation-guided general framework for transcriptome discovery, reconstruction and quantification in partially annotated genomes and compare it with existing annotation-guided and genome-guided transcriptome assembly methods. Our method, referred as Discovery and Reconstruction of Unannotated Transcripts (DRUT), can be used to enhance existing transcriptome assemblers, such as Cufflinks, as well as to accurately estimate the transcript frequencies...
2011: In Silico Biology
Nicholas Mancuso, Bassam Tork, Pavel Skums, Lilia Ganova-Raeva, Ion Măndoiu, Alex Zelikovsky
This paper addresses the problem of reconstructing viral quasispecies from next-generation sequencing reads obtained from amplicons (i.e., reads generated from predefined amplified overlapping regions). We compare the parsimonious and likelihood models for this problem and propose several novel assembling algorithms. The proposed methods have been validated on simulated error-free HCV and real HBV amplicon reads. The new algorithms have been shown to outperform the method of Prosperi et. al. Our experiments also show that viral quasispecies can be reconstructed in most cases more accurately from amplicon reads rather than shotgun reads...
2011: In Silico Biology
James Lara, John E Tavis, Maureen J Donlin, William M Lee, He-Jun Yuan, Brian L Pearlman, Gilberto Vaughan, Joseph C Forbi, Guo-Liang Xia, Yury E Khudyakov
Machine-learning methods in the form of Bayesian networks (BN), linear projection (LP) and self-organizing tree (SOT) models were used to explore association among polymorphic sites within the HVR1 and NS5a regions of the HCV genome, host demographic factors (ethnicity, gender and age) and response to the combined interferon (IFN) and ribavirin (RBV) therapy. The BN models predicted therapy outcomes, gender and ethnicity with accuracy of 90%, 90% and 88.9%, respectively. The LP and SOT models strongly confirmed associations of the HVR1 and NS5A structures with response to therapy and demographic host factors identified by BN...
2011: In Silico Biology
James Lara, Yury Khudyakov
Sequence heterogeneity substantially affects antigenic properties of the major epitope in the hepatitis C virus (HCV) NS3 protein. To facilitate protein engineering of NS3 antigens immunologically reactive with antibody against the broad diversity of HCV variants we constructed a set of Bayesian Networks (BN) for predicting antigenicity based on structural parameters. Using homology modeling, tertiary (3D) structures of NS3 variants with known antigenic properties were predicted. Energy force field estimated using the 3D-models was found to be most strongly associated with the antigenic properties...
2011: In Silico Biology
Z Dimitrova, D S Campo, S Ramachandran, G Vaughan, L Ganova-Raeva, Y Lin, J C Forbi, G Xia, P Skums, B Pearlman, Y Khudyakov
Hepatitis C Virus sequence studies mainly focus on the viral amplicon containing the Hypervariable region 1 (HVR1) to obtain a sample of sequences from which several population genetics parameters can be calculated. Recent advances in sequencing methods allow for analyzing an unprecedented number of viral variants from infected patients and present a novel opportunity for understanding viral evolution, drug resistance and immune escape. In the present paper, we compared three recent technologies for amplicon analysis: (i) Next-Generation Sequencing; (ii) Clonal sequencing using End-point Limiting-dilution for isolation of individual sequence variants followed by Real-Time PCR and sequencing; and (iii) Mass spectrometry of base-specific cleavage reactions of a target sequence...
2011: In Silico Biology
D S Campo, Z Dimitrova, J Lara, M Purdy, H Thai, S Ramachandran, L Ganova-Raeva, X Zhai, J C Forbi, C G Teo, Y Khudyakov
The detection of compensatory mutations that abrogate negative fitness effects of drug-resistance and vaccine-escape mutations indicates the important role of epistatic connectivity in evolution of viruses, especially under the strong selection pressures. Mapping of epistatic connectivity in the form of coordinated substitutions should help to characterize molecular mechanisms shaping viral evolution and provides a tool for the development of novel anti-viral drugs and vaccines. We analyzed coordinated variation among amino acid sites in 370 the hepatitis B virus (HBV) polymerase sequences using Bayesian networks...
2011: In Silico Biology
I V Astrakhantseva, D S Campo, A Araujo, C-G Teo, Y Khudyakov, S Kamili
Distinguishing between acute and chronic HCV infections is clinically important given that early treatment of infected patients leads to high rates of sustained virological response. Analysis of 2179 clonal sequences derived from hypervariable region 1 (HVR1) of the HCV genome in samples obtained from patients with acute (n = 49) and chronic (n = 102) HCV infection showed that intra-host HVR1 diversity was 1.8 times higher in patients with chronic than acute infection. Significant differences in frequencies of 5 amino acids (positions 5, 7, 12, 16 and 18) and the average genetic distances among intra-host HVR1 variants were found using analysis of molecular variance...
2011: In Silico Biology
P S Demenkov, T V Ivanisenko, N A Kolchanov, V A Ivanisenko
The ANDVisio tool is designed to reconstruct and analyze associative gene networks in the earlier developed Associative Network Discovery System (ANDSystem) software package. The ANDSystem incorporates utilities for automated extraction of knowledge from Pubmed published scientific texts, analysis of factographic databases, also the ANDCell database containing information on molecular-genetic events retrieved from texts and databases. ANDVisio is a new user's interface to the ANDCell database stored in a remote server...
2011: In Silico Biology
Andrey Palyanov, Sergey Khayrulin, Stephen D Larson, Alexander Dibert
The nematode C. elegans is the only animal with a known neuronal wiring diagram, or "connectome". During the last three decades, extensive studies of the C. elegans have provided wide-ranging data about it, but few systematic ways of integrating these data into a dynamic model have been put forward. Here we present a detailed demonstration of a virtual C. elegans aimed at integrating these data in the form of a 3D dynamic model operating in a simulated physical environment. Our current demonstration includes a realistic flexible worm body model, muscular system and a partially implemented ventral neural cord...
2011: In Silico Biology
Sergey A Lashin, Yury G Matushkin
In this paper we consider the recent advances in methodology for modeling of prokaryotic communities evolution and new features of the software package "Haploid evolutionary constructor" ( We show the principles of building complex computer models in our software tool. These models describe several levels of biological organization: genetic, metabolic, population, ecological. New features of the haploid evolutionary constructor include the modeling of gene networks and phage infections...
2011: In Silico Biology
Konstantin V Gunbin, Valentin V Suslov, Mikhail A Genaev, Dmitry A Afonnikov
SAMEM (System for Analysis of Molecular Evolution Modes), a web-based pipeline system for inferring modes of molecular evolution in genes and proteins (, is presented. Pipeline 1 performs analyses of protein-coding gene evolution; pipeline 2 performs analyses of protein evolution; pipeline 3 prepares datasets of genes and/or proteins, performs their primary analysis, and builds BLOSUM matrices; pipeline 4 checks if these genes really are protein-coding. Pipeline 1 has an all-new feature, which allows the user to obtain K(R)/K(C) estimates using several different methods...
2011: In Silico Biology
Y Y Vaskin, I V Khomicheva, E V Ignatieva, E E Vityaev
The task of automatic extraction of the hierarchical structure of eukaryotic gene regulatory regions is in the junction of the fields of biology, mathematics and information technologies. A solution of the problem involves understanding of sophisticated mechanisms of eukaryotic gene regulation and applying advanced data mining technologies. In the paper the integrated system, implementing a powerful relation mining of biological data method, is discussed. The system allows taking into account prior information about the gene regulatory regions that is known by the biologist, performing the analysis on each hierarchical level, searching for a solution from a simple hypothesis to a complex one...
2011: In Silico Biology
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