Abstract: Clustering techniques have received attention in many areas including engineering, medicine, biology and data mining. The purpose of clustering is to group together data points, which are close to one another. The K-means algorithm is one of the most widely used techniques for clustering. However, K-means has two shortcomings: dependency on the initial state and convergence to local optima and global solutions of large problems cannot found with reasonable amount of computation effort. In order to overcome local optima problem lots of studies done in clustering. This paper is presented an efficient hybrid evolutionary optimization algorithm based on combining Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO), called PSO-ACO, for optimally clustering N object into K clusters. The new PSO-ACO algorithm is tested on several data sets, and its performance is compared with those of ACO, PSO and K-means clustering. The simulation results show that the proposed evolutionary optimization algorithm is robust and suitable for handing data clustering.
Abstract: Mendelian Disease Genes represent a collection of single points of failure for the various systems they constitute. Such genes have been shown, on average, to encode longer proteins than 'non-disease' proteins. Existing models suggest that this results from the increased likeli-hood of longer genes undergoing mutations. Here, we show that in saturated mutagenesis experiments performed on model organisms, where the likelihood of each gene mutating is one, a similar relationship between length and the probability of a gene being lethal was observed. We thus suggest an extended model demonstrating that the likelihood of a mutated gene to produce a severe phenotype is length-dependent. Using the occurrence of conserved domains, we bring evidence that this dependency results from a correlation between protein length and the number of functions it performs. We propose that protein length thus serves as a proxy for protein cardinality in different networks required for the organism's survival and well-being. We use this example to argue that the collection of Mendelian Disease Genes can, and should, be used to study the rules governing systems vulnerability in living organisms.
Abstract: The goal of Gene Expression Analysis is to understand the processes that underlie the regulatory networks and pathways controlling inter-cellular and intra-cellular activities. In recent times microarray datasets are extensively used for this purpose. The scope of such analysis has broadened in recent times towards reconstruction of gene networks and other holistic approaches of Systems Biology. Evolutionary methods are proving to be successful in such problems and a number of such methods have been proposed. However all these methods are based on processing of genotypic information. Towards this end, there is a need to develop evolutionary methods that address phenotypic interactions together with genotypic interactions. We present a novel evolutionary approach, called Phenomic algorithm, wherein the focus is on phenotypic interaction. We use the expression profiles of genes to model the interactions between them at the phenotypic level. We apply this algorithm to the yeast sporulation dataset and show that the algorithm can identify gene networks with relative ease.
Abstract: A computational platform is presented in this
contribution. It has been designed as a virtual laboratory to be used
for exploring optimization algorithms in biological problems. This
platform is built on a blackboard-based agent architecture. As a test
case, the version of the platform presented here is devoted to the
study of protein folding, initially with a bead-like description of the
chain and with the widely used model of hydrophobic and polar
residues (HP model). Some details of the platform design are
presented along with its capabilities and also are revised some
explorations of the protein folding problems with different types of
discrete space. It is also shown the capability of the platform to
incorporate specific tools for the structural analysis of the runs in
order to understand and improve the optimization process.
Accordingly, the results obtained demonstrate that the ensemble of
computational tools into a single platform is worthwhile by itself,
since experiments developed on it can be designed to fulfill different
levels of information in a self-consistent fashion. By now, it is being
explored how an experiment design can be useful to create a
computational agent to be included within the platform. These
inclusions of designed agents –or software pieces– are useful for the
better accomplishment of the tasks to be developed by the platform.
Clearly, while the number of agents increases the new version of the
virtual laboratory thus enhances in robustness and functionality.
Abstract: Recent advances in both the testing and verification of software based on formal specifications of the system to be built have reached a point where the ideas can be applied in a powerful way in the design of agent-based systems. The software engineering research has highlighted a number of important issues: the importance of the type of modeling technique used; the careful design of the model to enable powerful testing techniques to be used; the automated verification of the behavioural properties of the system; the need to provide a mechanism for translating the formal models into executable software in a simple and transparent way. This paper introduces the use of the X-machine formalism as a tool for modeling biology inspired agents proposing the use of the techniques built around X-machine models for the construction of effective, and reliable agent-based software systems.
Abstract: Understanding the cell's large-scale organization is an interesting task in computational biology. Thus, protein-protein interactions can reveal important organization and function of the cell. Here, we investigated the correspondence between protein interactions and function for the yeast. We obtained the correlations among the set of proteins. Then these correlations are clustered using both the hierarchical and biclustering methods. The detailed analyses of proteins in each cluster were carried out by making use of their functional annotations. As a result, we found that some functional classes appear together in almost all biclusters. On the other hand, in hierarchical clustering, the dominancy of one functional class is observed. In the light of the clustering data, we have verified some interactions which were not identified as core interactions in DIP and also, we have characterized some functionally unknown proteins according to the interaction data and functional correlation. In brief, from interaction data to function, some correlated results are noticed about the relationship between interaction and function which might give clues about the organization of the proteins, also to predict new interactions and to characterize functions of unknown proteins.
Abstract: This article examines the nature and structure of ecological education of biology specialists in Kazakhstan. Also characterizes the ecological education in high school and specific features in training of biology specialists.
Abstract: A number of competing methodologies have been developed
to identify genes and classify DNA sequences into coding
and non-coding sequences. This classification process is fundamental
in gene finding and gene annotation tools and is one of the most
challenging tasks in bioinformatics and computational biology. An
information theory measure based on mutual information has shown
good accuracy in classifying DNA sequences into coding and noncoding.
In this paper we describe a species independent iterative
approach that distinguishes coding from non-coding sequences using
the mutual information measure (MIM). A set of sixty prokaryotes is
used to extract universal training data. To facilitate comparisons with
the published results of other researchers, a test set of 51 bacterial
and archaeal genomes was used to evaluate MIM. These results
demonstrate that MIM produces superior results while remaining
species independent.
Abstract: This study aims to conduct a preliminary investigation to determine the topic to be focused in developing Virtual Laboratory For Biology (VLab-Bio). Samples involved in answering the questionnaire are form five students (equivalent to A-Level) and biology teachers. Time and economical resources for the setting up and construction of scientific laboratories can be solved with the adaptation of virtual laboratories as an educational tool. Thus, it is hoped that the proposed virtual laboratory will help students to learn the abstract concepts in biology. Findings show that the difficult topic chosen is Cell Division and the learning objective to be focused in developing the virtual lab is “Describe the application of knowledge on mitosis in cloning".
Abstract: Traditionally, VLSI implementations of spiking
neural nets have featured large neuron counts for fixed computations
or small exploratory, configurable nets. This paper presents the
system architecture of a large configurable neural net system
employing a dedicated mapping algorithm for projecting the targeted
biology-analog nets and dynamics onto the hardware with its
attendant constraints.
Abstract: Detecting protein-protein interactions is a central problem in computational biology and aberrant such interactions may have implicated in a number of neurological disorders. As a result, the prediction of protein-protein interactions has recently received considerable attention from biologist around the globe. Computational tools that are capable of effectively identifying protein-protein interactions are much needed. In this paper, we propose a method to detect protein-protein interaction based on substring similarity measure. Two protein sequences may interact by the mean of the similarities of the substrings they contain. When applied on the currently available protein-protein interaction data for the yeast Saccharomyces cerevisiae, the proposed method delivered reasonable improvement over the existing ones.
Abstract: We have developed a computer program consisting of
6 subtests assessing the children hand dexterity applicable in the
rehabilitation medicine. We have carried out a normative study on a
representative sample of 285 children aged from 7 to 15 (mean age
11.3) and we have proposed clinical standards for three age groups
(7-9, 9-11, 12-15 years). We have shown statistical significance of
differences among the corresponding mean values of the task time
completion. We have also found a strong correlation between the task
time completion and the age of the subjects, as well as we have
performed the test-retest reliability checks in the sample of 84
children, giving the high values of the Pearson coefficients for the
dominant and non-dominant hand in the range 0.740.97 and
0.620.93, respectively.
A new MATLAB-based programming tool aiming at analysis of
cardiologic RR intervals and blood pressure descriptors, is worked
out, too. For each set of data, ten different parameters are extracted: 2
in time domain, 4 in frequency domain and 4 in Poincaré plot
analysis. In addition twelve different parameters of baroreflex
sensitivity are calculated. All these data sets can be visualized in time
domain together with their power spectra and Poincaré plots. If
available, the respiratory oscillation curves can be also plotted for
comparison. Another application processes biological data obtained
from BLAST analysis.
Abstract: The importance for manipulating an incorporated
scaffold and directing cell behaviors is well appreciated for tissue
engineering. Here, we developed newly nano-topographic oxidized
silicon nanosponges capable of being various chemical modifications
to provide much insight into the fundamental biology of how cells
interact with their surrounding environment in vitro. A wet etching
technique is exerted to allow us fabricated the silicon nanosponges in a
high-throughput manner. Furthermore, various organo-silane
chemicals enabled self-assembled on the surfaces by vapor deposition.
We have found that Chinese hamster ovary (CHO) cells displayed
certain distinguishable morphogenesis, adherent responses, and
biochemical properties while cultured on these chemical modified
nano-topographic structures in compared with the planar oxidized
silicon counterparts, indicating that cell behaviors can be influenced
by certain physical characteristic derived from nano-topography in
addition to the hydrophobicity of contact surfaces crucial for cell
adhesion and spreading. Of particular, there were predominant
nano-actin punches and slender protrusions formed while cells were
cultured on the nano-topographic structures. This study shed potential
applications of these nano-topographic biomaterials for controlling
cell development in tissue engineering or basic cell biology research.
Abstract: IT infrastructures are becoming more and more
difficult. Therefore, in the first industrial IT systems, the P2P
paradigm has replaced the traditional client server and methods of
self-organization are gaining more and more importance. From the
past it is known that especially regular structures like grids may
significantly improve the system behavior and performance. This
contribution introduces a new algorithm based on a biologic
analogue, which may provide the growth of several regular structures
on top of anarchic grown P2P- or social network structures.
Abstract: Term Extraction, a key data preparation step in Text
Mining, extracts the terms, i.e. relevant collocation of words,
attached to specific concepts (e.g. genetic-algorithms and decisiontrees
are terms associated to the concept “Machine Learning" ). In
this paper, the task of extracting interesting collocations is achieved
through a supervised learning algorithm, exploiting a few
collocations manually labelled as interesting/not interesting. From
these examples, the ROGER algorithm learns a numerical function,
inducing some ranking on the collocations. This ranking is optimized
using genetic algorithms, maximizing the trade-off between the false
positive and true positive rates (Area Under the ROC curve). This
approach uses a particular representation for the word collocations,
namely the vector of values corresponding to the standard statistical
interestingness measures attached to this collocation. As this
representation is general (over corpora and natural languages),
generality tests were performed by experimenting the ranking
function learned from an English corpus in Biology, onto a French
corpus of Curriculum Vitae, and vice versa, showing a good
robustness of the approaches compared to the state-of-the-art Support
Vector Machine (SVM).
Abstract: The objective of our work is to develop a new approach for discovering knowledge from a large mass of data, the result of applying this approach will be an expert system that will serve as diagnostic tools of a phenomenon related to a huge information system. We first recall the general problem of learning Bayesian network structure from data and suggest a solution for optimizing the complexity by using organizational and optimization methods of data. Afterward we proposed a new heuristic of learning a Multi-Entities Bayesian Networks structures. We have applied our approach to biological facts concerning hereditary complex illnesses where the literatures in biology identify the responsible variables for those diseases. Finally we conclude on the limits arched by this work.
Abstract: From the beginning of creation, human being has ever
fought against the ecosystem by changes has made in environment.
The most environmental changes on the nature have been done after
starting the concentrated life in the same region. Dams are one of the
most important buildings in water resources and transferring. These
buildings have been made from old times without access to
hydrological, hydraulically, hydro mechanical information. Dams
have positive and negative effects on environment. Constructing a
dam relatively causes equal ecological consequences. According to
different criteria, environmental effects of dams can lead short term
and long term damages. These effects may influence on the situation
and treatment of meteorology, biology, culture, ancient works, etc
and severely causes to change and complicate it. So considering
importance of positive effects of dam construction, it is necessary to
minimize negative environmental effects of dams to achieve a stable
development. In this article the considered effects and their solutions
in influencing on assessment of destructive environmental effects of
dams construction have been surveyed and presented.
Abstract: Chemical reaction and diffusion are important phenomena in quantitative neurobiology and biophysics. The knowledge of the dynamics of calcium Ca2+ is very important in cellular physiology because Ca2+ binds to many proteins and regulates their activity and interactions Calcium waves propagate inside cells due to a regenerative mechanism known as calcium-induced calcium release. Buffer-mediated calcium diffusion in the cytosol plays a crucial role in the process. A mathematical model has been developed for calcium waves by assuming the buffers are in equilibrium with calcium i.e., the rapid buffering approximation for a one dimensional unsteady state case. This model incorporates important physical and physiological parameters like dissociation rate, diffusion rate, total buffer concentration and influx. The finite difference method has been employed to predict [Ca2+] and buffer concentration time course regardless of the calcium influx. The comparative studies of the effect of the rapid buffered diffusion and kinetic parameters of the model on the concentration time course have been performed.
Abstract: Protein and Esterase electrophoresis were used to
genetically identify two Saudi tick species. Engorged females of the
camel tick Hyalomma dromedarii (Koch) (Acari: Ixodidae) and the
cattle tick Boophilus annulatus (Say) (Acari: Ixodidae) ticks
collected from infested camels and cattle in the animals resting
house at Hail region in KSA were used. The results showed that
there are a variation in both of protein and esterase activity levels and
a high polymorphism within and between the genera and species of
Hyalomma and Boophilus . In conclusion, the protein and esterase
electrophoretic analysis used in the present study could successfully
distinguish among tick species, commonly found in Saudi Arabia.
Abstract: The problem on the conservation programme of the Royal Thai Navy Sea Turtle Nursery, Phang-nga Province, Thailand is high mortality rate of juvenile green sea turtle (Cheloniamydas) on nursing period. So, during May to October 2012, postmortem examinations of juvenile green sea turtle were performed to determine the causes of dead. Fresh tissues of postmortem of 15 juvenile green sea turtles (1-3 months old) were investigated using paraffin section technique. The results showed normal ultrastructure of all tissue organs. These instances reviewed the health and stability of the environments in which juvenile green sea turtles live and concern for the survival rate. The present article also provides guidance for a review of the biology, guidelines for appropriate postmortem tissue, normal histology and sampling collection and procedures. The data also provides information for conservation of this endangered species in term of acknowledging and encouraging people to protect the animals and their habitats in nature.