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