Prof. Eric Mwambene
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| Position: | Associate Professor |
| Department: | Department of Mathematics |
| Faculty: | Faculty of Natural Sciences |
| Qualifications: | DSc (Vienna), MSc (UZ), MSc (London), BSc (Hons)(Unima) |
| My publications in this repository | |
| More about me: | here and here |
| Tel: | 021 959 3021 |
| Fax: | 021 959 1241 |
| Email: | emwambene@uwc.ac.za |
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Item Self-similarity of human protein interaction networks: a novel strategy of distinguishing proteins(2015) Fadhal, Emad; Gamieldien, Junaid; Mwambene, EricThe successful determination of reliable protein interaction networks (PINs) in several species in the post-genomic era has hitherto facilitated the quest to understanding systems and structural properties of such networks. It is envisaged that a clearer understanding of their intrinsic topological properties would elucidate evolutionary and biological topography of organisms. This, in turn, may inform the understanding of diseases’ aetiology. By analysing sub-networks that are induced in various layers identified by zones defined as distance from central proteins, we show that zones of human PINs display self-similarity patterns. What is observed at a global level is repeated at lower levels of inducement. Furthermore, it is observed that these levels of strength point to refinement and specialisations in these layers. This may point to the fact that various levels of representations in the self-similarity phenomenon offer a way of measuring and distinguishing the importance of proteins in the network. To consolidate our findings, we have also considered a gene co-expression network and a class of gene regulatory networks in the same framework. In all cases, the phenomenon is significantly evident. In particular, the truly unbiased regulatory networks show finer level of articulation of self-similarity.Item An assessment of the age reporting in Tanzania population census(Academic Research Publishing, 2012) Mwambene, Eric; Appunni, Sathiya Susuman; Hamisi, Hamisi F.; Lougue, Siaka; Regassa, Nigatu; Ogujiuba, KanayoThe objective of this paper is to provide data users with a worldwide assessment of the age reporting in the Tanzania Population Census 2012 data. Many demographic and socio-economic data are age-sex attributed. However, a variety of irregularities and misstatements are noted with respect to age-related data and sex ratio data because of its biological differences between the genders. Noting the misstatement / misreporting, inconsistence of age data regardless of its significant importance in demographic and epidemiological studies, this study assess the quality of the 2012 Tanzania Population and Housing Census data relative to age. Data were downloaded from Tanzania National Bureau of Statistics. Age heaping and digit preference were measured using summary indices viz., Whipple‟s index, Myers‟ blended index, and Age-Sex Accuracy index. The recorded Whipple‟s index for both sexes was 154.43, where males had the lower index of about 152.65 while females had the higher index of about 156.07. For Myers‟ blended index, the prefrences were at digits „0‟ and „5‟ while avoidance were at digits „1‟ and „3‟ for both sexes. Finally, the age-sex index stood at 59.8 where the sex ratio score was 5.82, and the age ratio scores were 20.89 and 21.4 for males and female respectively. The evaluation of the 2012 Population Housing Censes data using the demographic techniques has qualified the data as of poor quality as a result of systematic heaping and digit preferences/avoidances in recorded age. Thus, innovative methods in data collection along with measuring and minimizing errors using statistical techniques should be used to ensure accuracy of age data.