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In figure 4.1 above, which is the graph of the empirical runtime of STGEMS compared with those of MEME, WEEDER, GEMS, EXMOTIF and RISOTTO, It can be seen that MEME had the lowest performance among all the other tools compared since its running time over the set of the selected input was the highest, that is, the execution time of MEME in all instances was higher than the other tools. On the other hand, STGEMS had the lowest empirical run time which implied that it is a time efficient algorithm. The more efficient an algorithms is, the lower its empirical runtime.

4.2 PERFORMANCE OF STGEMS IN MINING BIOLOGICALLY

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between the two boxes.

Yuda et al. (2009) also show that experimentally, TAGCTA-100 to1500-TAGCCA and TAGCTA-100 to1500-TGGCTA are those structured motifs used in their co-regulation.

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Table 4.2. Set of genes from Flueck et al.

Accession No Description PFF0645c

PFI0265c PFE0075c PFE0080c PFC0120w MAL7P1.208 PFI1730w PF14_0102 PFD0295c MAL7P1.119 PFI1445w

Plasmodium falciparum 3D7 , integral membrane protein, putative

Plasmodium falciparum 3D7, high molecular weight rhoptry protein

Plasmodium falciparum 3D7, rhoptry-associated protein 3 Plasmodium falciparum 3D7, rhoptry-associated protein 2

Plasmodium falciparum 3D7 , cytoadherence linked asexual protein 3.1

Plasmodium falciparum 3D7, rhoptry-associated membrane antigen

Plasmodium falciparum 3D7, cytoadherence linked asexual protein 9

Plasmodium falciparum 3D7, rhoptry-associated protein 1 Plasmodium falciparum 3D7 , apical sushi protein

Plasmodium falciparum 3D7 , rhoptry-associated leucine zipper-like protein 1

Plasmodium falciparum 3D7, high molecular weight rhoptry protein 2

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Table 4.2 shows the accession number of the genes and their equivalent description. The accession numbers are unique and they uniquely identify each gene in all the gene databases, such as http://geneontology.org, http://plasmodb.org, http://genebank.org etc.

The standard NCBI format for naming genes accession numbers is the short name of the organism as the first character and then a sequence generated number. For example in PFI1445w, the PF stands for Plasmodium Falciparum.

The gene accession numbers starting with MAL stands for Malaria, the old format for naming gene accession number uses the disease caused by the organism instead of the organism’s short name.

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Table 4.3. Output from running the algorithms on the DNA sequences in table 4.2 IDENTIFIED BY

Motifs RISOTTO EXMOTIF WEEDER MEME GEMS STGEMS

GGTGCG YES NO NO NO NO NO

CGTGCG NO NO NO NO NO NO

CTGCA YES NO NO NO YES YES

GTGCA YES YES YES YES YES YES

ATGCA NO YES YES YES YES YES

AGTGCG NO NO NO NO YES YES

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Table 4.3 shows the output of running the six algorithms using a data set which has been biologically proven to contain consensus motifs or potential binding sites. The output of each algorithm was scanned for the occurrence of these consensus motifs shown in the first column of table 4.3. that is the consensus motifs. These consensuses have been shown by Flueck et al. (2010) to be valid binding sites in P.falciparum using biological experimental methods. The result of the analysis revealed that MEME,WEEDER and EXMOTIF are similar both in the number and type of motif discovered, For instance, out of the six motifs scanned for, only two were discovered by the three tools i.e. ‘GTGCA’,

‘ATGCA’ while ‘GGTGCG’, ‘CGTGCG’, ‘CTGCA’ and ‘AGTGCG’ were not found.

RISOTTO exhibited a unique behaviour, the type and number of motifs discovered did not correspond to those discovered by the other tools. It found three motifs out of the six scanned for. GEMS and STGEMS were similar in the type and number of motifs found, they both discovered ‘CTGCA’, ‘GTGCA’, ‘ATGCA’ and ‘AGTGCG’. This similarity between STGEMS and GEMS is because they both utilized the same mechanism in their methodology, that is, the hypergeometric motif enrichment search mechanism. The main advantage STGEMS has over GEMS is in the speed of execution and in its ability to mine both simple and structured motifs for the challenging genome of P.falciparum.

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Table 4.4. Set of genes from the Mosquito invasive stage of malaria parasite.

Accession No Description PF08_0136b

PFC0905c PFL0550w PFC0640w PFD0425w PF08_0030 PFL2135c MAL13P1.203 PF10_0027 PFL2510w PF13_0355 PFD0435c PFE0360c PF14_0040 PFF0975c PF10_0302 PF10_0303 PFC0420w PFI1145w

Plasmodium falciparum 3D7 , von Willebrand factor A-domain related protein

Plasmodium falciparum 3D7, oocyst capsule protein Plasmodium falciparum 3D7, HSP20-like chaperone

Plasmodium falciparum 3D7,CSP and TRAP-related protein

Plasmodium falciparum 3D7 , sporozoite invasion-associated protein 1, putative

Plasmodium falciparum 3D7, conserved Plasmodium protein, unknown function

Plasmodium falciparum 3D7, conserved Plasmodium protein, unknown function

Plasmodium falciparum 3D7 , secreted ookinete protein, putative Plasmodium falciparum 3D7,conserved Plasmodium protein, unknown function

Plasmodium falciparum 3D7, chitinase

Plasmodium falciparum 3D7, secreted ookinete protein Plasmodium falciparum 3D7, conserved Plasmodium protein Plasmodium falciparum 3D7, conserved Plasmodium protein Plasmodium falciparum 3D7, secreted ookinete adhesive protein Plasmodium falciparum 3D7, conserved Plasmodium protein Plasmodium falciparum 3D7, 28 kDa ookinete surface protein

Plasmodium falciparum 3D7, 25 kDa ookinete surface antigen precursor

Plasmodium falciparum 3D7, calcium dependent protein kinase 3 Plasmodium falciparum 3D7, perforin like protein 3

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Table 4.5: Output from running the algorithms on the DNA sequences in table 4.4 IDENTIFIED BY

Motifs RISOTTO EXMOTIF WEEDER MEME GEMS STGEMS

TAGCTA YES NO YES NO NO NO

TGGCTA NO NO NO NO NO NO

TAGCCA NO NO NO NO NO NO

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From table 4.3, it is can be observed that many of the experimentally extracted motifs were also mined by GEMS and by extension, our novel algorithm, STGEMS. This was not the same finding in table 4.5, as none of the two structured motifs was found by GEMS nor by STGEMS. Only RISOTTO and WEEDER discovered one motif each that is, ‘TAGCTA’ and ‘TAGCTA’ respectively. The other three tools, that is, MEME, GEMS and EXMOTIF could not also detect any of the motifs.

The observation recorded in table 4.5 gave the understanding that a number of fine tunings, which are not necessarily algorithmic, are needed to effectively mine the desired structured motifs in the set of table 4.4.

4.3 EVALUATION OF PREDICTIVE ACCURACY OF STGEMS