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1.1 BACKGROUND INFORMATION
Malaria is one of the planet's deadliest diseases and one of the leading causes of sickness and death in the developing world. Africa has suffered and is still suffering from the adverse socio-economic effects of malaria; It is intimately connected with poverty. Judged as both a root cause and a consequence of poverty, it is most intractable for the poorest countries in the world. According to GSK’s (GlaxoSmithKline) Corporate Responsibility Report 2007, it affects the health and economic growth of nations and individuals alike and is costing Africa about $12 billion a year in economic output. It has a greater impact on Africa's human resources than simple lost earnings. Another indirect cost of malaria is the human pain and suffering caused by the disease. It also hampers children's schooling and social development through both absenteeism and permanent neurological and other damage associated with severe episodes of the disease (© 2008 Millennium Promise). According to WHO’s (World Health Organization) World Malaria Report 2008, there were an estimated 247 million malaria cases worldwide in 2006, of which 91% or 230 million were due to Plasmodium falciparum. The vast majority of cases (86%) were in the African Region, followed by the South-East Asia (9%) and Eastern Mediterranean regions (3%) as shown in figure 1.1.
There are four major human malaria strains (Plasmodium falciparum, Plasmodium vivax, Plasmodium ovale, Plasmodium malariae). Plasmodium falciparum is the most common and
deadly form. The percentage of malaria cases due to Plasmodium falciparum exceeded 75% in most African countries but only in a few countries outside Africa. In Africa, Nineteen of the most populous countries accounted for 90% of estimated cases in 2006 with Nigeria having the highest percent of the 90% estimated cases (WHO’s World Malaria Report 2008) as shown in figure 1.2.
Fig 1.1 Estimated incidence of malaria per 1000, 2006 (WHO’s World Malaria Report 2008)
Fig 1.2 Nineteen countries estimated to have 90% of cases in African Region, 2006 (WHO’s World Malaria Report 2008)
This calls for increased speed in the search for more potent/effective cure that will preserve the lives of many. Chloroquine and most anti-malaria drugs are fast becoming in-effective as the parasite has grown resistance to them. Therefore, there is a huge need to discover and validate new drug or vaccine targets to enable the development of new treatments for malaria (Bulashevska, S. et al; 2007).
This project work is aimed at building a publicly accessible database through the use of a relational database architecture that will house Plasmodium falciparum genome sequence data and the results that we obtained by applying in-silico tools for quick access such that researchers can integrate this resource with other relevant data sets, and exploit the resulting information for functional studies, including identification of novel drug targets and candidate vaccine antigens.
We believe that the experimental results that will be obtained from our data will drive work in malaria research that will quicken the discovery pipeline of drugs and vaccines.
1.2 STATEMENT OF THE PROBLEM
KEGG database is mainly developed using in-silico analysis, while BioCyc is experimentally curated but strongly in many cases confirmed the in-silico results displayed on the metabolic
network of KEGG. Therefore, the database, we implemented (afriPFdb), in this project work is to display our findings developed using in-silico tools for experimental validation.
One other important lacking utility from other databases is informative detail on Plasmodium falciparum’s tRNAs’ (transfer RNA) important sites for drug targets. Transfer RNA carries amino acids to the ribosomes for incorporation into a protein. We also incorporated this into our database ‘The African Plasmodium falciparum Database’ (afriPFdb).
1.3 AIM AND OBJECTIVES
The aim of this research work is to build a publicly accessible database that will house in-depth and up-to-date information on Plasmodium falciparum from built in-silico tools for easy and quick access by malaria researchers.
This aim will be achieved through the following objectives;
i. To design and build a well structured database that will enhance an ‘easy to find’ presentation of available information.
ii. To design a simple and easy to navigate website with adequate and correct biological data on Plasmodium falciparum.
iii. To build a database to accommodate constant updates as is the nature of biological data.
iv. To design a website to house and publish the findings on malaria research which can then be validated experimentally.
In developing afriPFdb, the following methods were adopted; the web pages (frontend) were designed with ‘Web Page Maker’ and then exported to HTML (Hyper Text Markup Language).
The middle ware (i.e. web ser
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