57 research outputs found
Colored Petri Net: Its application to Sucrose Biosynthesis Pathway in Plasmodium falciparum
Sucrose plays major role as macromolecule used in organisms including Plasmodium falciparum (P.f.) to generate glucose for energy production in the glycolysis pathway. A metabolic pathway is a series of chemical reactions, which goes through various intermediate compounds to transform input compounds into a product. In this work, we modelled a metabolic pathway in Plasmodium falciparum using Colored Petri Net Markup Language (CPNML). The model was used to examine the dynamic behavior of the sucrose biosynthesis pathway which shows the interactions between the metabolites and the reactions in the sucrose biosynthesis pathway of Plasmodium falciparum. We further analyzed the model for its structural and quantitative properties using Petri Net theory. Our model gives more insight to the structure of the pathway and helps to improve our understanding of the biological processes within this pathway.Keywords: Sucrose, Colored Petri Net, Plasmodium falciparu
Design and Implementation of Text To Speech Conversion for Visually Impaired People
A Text-to-speech synthesizer is an application that converts text into spoken word, by analyzing and processing the text using Natural Language Processing (NLP) and then using Digital Signal Processing (DSP) technology to convert this processed text into synthesized speech representation of the text. Here, we developed a useful text-to-speech synthesizer in the form of a simple application that converts inputted text into synthesized speech and reads out to the user which can then be saved as an mp3.file. The development of a text to speech synthesizer will be of great help to people with visual impairment and make making through large volume of text easie
Computational identification of signalling pathways in Plasmodium falciparum
Malaria is one of the world’s most common and serious diseases causing death of about 3 million people
each year. Its most severe occurrence is caused by the protozoan Plasmodium falciparum. Reports have
shown that the resistance of the parasite to existing drugs is increasing. Therefore, there is a huge and
urgent need to discover and validate new drug or vaccine targets to enable the development of new
treatments for malaria. The ability to discover these drug or vaccine targets can only be enhanced from
our deep understanding of the detailed biology of the parasite, for example how cells function and how
proteins organize into modules such as metabolic, regulatory and signal transduction pathways. It has
been noted that the knowledge of signalling transduction pathways in Plasmodium is fundamental to aid
the design of new strategies against malaria. This work uses a linear-time algorithm for finding paths in a
network under modified biologically motivated constraints. We predicted several important signalling
transduction pathways in Plasmodium falciparum. We have predicted a viable signalling pathway
characterized in terms of the genes responsible that may be the PfPKB pathway recently elucidated in
Plasmodium falciparum. We obtained from the FIKK family, a signal transduction pathway that ends up on
a chloroquine resistance marker protein, which indicates that interference with FIKK proteins might
reverse Plasmodium falciparum from resistant to sensitive phenotype. We also proposed a hypothesis
that showed the FIKK proteins in this pathway as enabling the resistance parasite to have a mechanism
for releasing chloroquine (via an efflux process). Furthermore, we also predicted a signalling pathway
that may have been responsible for signalling the start of the invasion process of Red Blood Cell (RBC) by
the merozoites. It has been noted that the understanding of this pathway will give insight into the
parasite virulence and will facilitate rational vaccine design against merozoites invasion. And we have a
host of other predicted pathways, some of which have been used in this work to predict the functionality
of some proteins
Modeling of the Glycolysis Pathway in Plasmodium falciparum using Petri Nets
Malaria is one of the deadly diseases, which affects a large number of the world’s population. The Plasmodium falciparum parasite during erythrocyte stages produces its energy mainly through anaerobic glycolysis, with pyruvate being converted into lactate. The glycolysis metabolism in P. falci-parum is one of the important metabolic pathways of the parasite because the parasite is entirely dependent on it for energy. Also, several glycolytic enzymes have been proposed as drug targets. Petri nets (PNs) have been recognized as one of the important models for representing biological pathways. In this work, we built a qualitative PN model for the glycolysis pathway in P. falciparum and analyzed the model for its structural and quantitative properties using PN theory. From PlasmoCyc files, a total of 11 reactions were extracted; 6 of these were reversible and 5 were irreversible. These reactions were catalyzed by a total number of 13 enzymes. We extracted some of the essential reactions in the pathway using PN model, which are the possible drug targets without which the pathway cannot function. This model also helps to improve the understanding of the biological processes within this pathway
SIMULATION AND ANALYSIS OF PENTOSE PHOSPHATE PATHWAY IN PLASMODIUM FALCIPARUM USING COLORED PETRI NETS MODEL
Plasmodium falciparum is a protozoan parasite and the deadliest of five human malaria
species which is responsible for the majority of malaria related deaths in humans. The
erythrocytes’ stage of Plasmodium falciparum depend on Pentose Pathway as an alternative
source of energy and it releases electrons used in protecting the Plasmodium falciparum from
its host. Colored Petri Net has been recognized as one of the important models in modelling
and analyzing biological pathways. It is an accurate qualitative and quantitative modelling
tool for modeling complex biological systems. In this work, the modeling of the pentose
phosphate pathway in Plasmodium falciparum is presented using the Petri Net Markup
Language (PNML). The Colored Petri Net (CPN) models based on the Petri Net
representation and the conservation and kinetic equations were used to examine the dynamic
behavior of the metabolic pathway. The usefulness of Petri Nets is demonstrated for the
quantitative analysis of the pathway. We obtained data from Biocyc database. The
constructed model was viewed through the Colored Petri Net Tool (CPN tool 4.0). Specific
drug targets called the essential reactions within the pathway were identified, listed and
proposed. These essential reactions would alter the functioning of the pathway which would
affect the energy and protection needs of the parasite therefore leading to the death of the
parasite in the human red blood cell
In Silico Gene Regulatory Network of the Maurer’s Cleft Pathway in Plasmodium falciparum
The Maurer’s clefts (MCs) are very important for the survival of Plasmodium falciparum within an infected cell as they are induced by the parasite itself in the erythrocyte for protein trafficking. The MCs form an interesting part of the parasite’s biology as they shed more light on how the parasite remodels the erythrocyte leading to host pathogenesis and death. Here, we predicted and analyzed the genetic regulatory network of genes identified to belong to the MCs using regularized graphical Gaussian model. Our network shows four major activators, their corresponding target genes, and predicted binding sites. One of these master activators is the serine repeat antigen 5 (SERA5), predominantly expressed among the SERA multigene family of P. falciparum, which is one of the blood-stage malaria vaccine candidates. Our results provide more details about functional interactions and the regulation of the genes in the MCs’ pathway of P. falciparum
Soft Clustering Technique on Academics Performance Evaluation
Clustering techniques are unsupervised learning methods of mining complex and multi-dimensional data sets such that observations in the same cluster are similar in some sense. The student academic performance evaluation problem can be considered as a clustering problem where clusters are formed on the basis of students intelligence. Choosing the right clustering technique for a given dataset is a research challenge. Therefore,intelligence-based grouping is essential for maintaining the homogeneity of the group; otherwise it would be difficult to provide good educational recommendation to the highly diverse student population. Homogenous grouping of students with similar result ranking into classes would further make student academic performance analysis detailed and sufficient for recommendation. Grouping of students using Fuzzy C-Means (FCM) techniques with the level of their degree of membership into different clusters allows for overlapping of boundaries and resolve sharp boundary problems as opposed to crisp-based method. FCM technique will reveal the degree of membership trend in the clusters which is the focus of this work. In this work, we implemented Soft clustering technique (Fuzzy CMeans) in C++ for student academic performance analysis. This will proffer recommendations that will enhance student performance
In Silico Gene Regulatory Network of the Maurer’s Cleft Pathway in Plasmodium falciparum
The Maurer’s clefts (MCs) are very important for the survival of Plasmodium falciparum within an infected cell as they are induced by the parasite itself in the erythrocyte for protein trafficking. The MCs form an interesting part of the parasite’s biology as they shed more light on how the parasite remodels the erythrocyte leading to host pathogenesis and death. Here, we predicted and analyzed the genetic regulatory network of genes identified to belong to the MCs using regularized graphical Gaussian model. Our network shows four major activators, their corresponding target genes, and predicted binding sites. One of these master activators is the serine repeat antigen 5 (SERA5), predominantly expressed among the SERA multigene family of P. falciparum, which is one of the blood-stage malaria vaccine candidates. Our results provide more details about functional interactions and the regulation of the genes in the MCs’ pathway of P. falciparum
Colored Petri Net Modeling of the Sucrose Biosynthesis Pathway in Plasmodium falciparum
Suuose is an imp01-tant macromolecule that is
used in o1·ganisms including Plasmodium falciparum (P.f) to
genemte glucose which is used f01· ene1·gy production in the
glycolysis pathway. In numerous 1·eseai-ch projects on
modelling and analyzing biological pathways, Petd net has
been 1·ecognized as a pmmising method f01· 1·ep1·esenting
biological pathways. A metabolic pathway is an
inte1-connected sedes of enzymatic 1·eactions that occm·
within a cell. It consists of consecutive chemical 1·eactions,
which tmnsf01·m input compound(s) (substmtes) via several
inte1·mediate compounds into an output compound
(]). This pape1· focuses on the use of Col01·ed Petd
Net to construct an in-silico metabolic netw01·k that shows
the interactions between the metabolites and the 1·eactions
in the suuose biosynthesis pathway of Plasmodium
falciparum (P.f) and fm·the1· analyze the model fo1· its
structural and quantitative pmpe1-ties using Petd net
theo1·y. Om· model gives mo1·e insight to the structure of the
pathway and helps to improve om· understanding of the
biological processes within this pathway
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