Browsing by Author "Gakii, Consolata"

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    Annotations of novel antennae-expressed genes in male Glossina morsitans morsitans tsetse flies
    (Plos 1, 2022-08) Bwana, Billiah K.; Mireji, Paul O.; Obiero, George F.; Gakii, Consolata; Akoth, Modesta O.; Mugweru, Julius N.; Nyabuga, Franklin N.; Wachira, Benson M.; Bateta, Rosemary; Ng’ang’a, Margaret M.; Hassanali, Ahmed
    Tsetse flies use antennal expressed genes to navigate their environment. While most canonical genes associated with chemoreception are annotated, potential gaps with important antennal genes are uncharacterized in Glossina morsitans morsitans. We generated antennae-specific transcriptomes from adult male G. m. morsitans flies fed/unfed on bloodmeal and/or exposed to an attractant (ε-nonalactone), a repellant (δ-nonalactone) or paraffin diluent. Using bioinformatics approach, we mapped raw reads onto G. m. morsitans geneset from VectorBase and collected un-mapped reads (constituting the gaps in annotation). We de novo assembled these reads (un-mapped) into transcript and identified corresponding genes of the transcripts in G. m. morsitans gene-set and protein homologs in UniProt protein database to further annotate the gaps. We predicted potential protein-coding gene regions associated with these transcripts in G. m. morsitans genome, annotated/curated these genes and identified their putative annotated orthologs/homologs in Drosophila melanogaster, Musca domestica or Anopheles gambiae genomes. We finally evaluated differential expression of the novel genes in relation to odor exposures relative to no-odor control (unfed flies). About 45.21% of the sequenced reads had no corresponding transcripts within G. m. morsitans gene-set, corresponding to the gap in existing annotation of the tsetse fly genome. The total reads assembled into 72,428 unique transcripts, most (74.43%) of which had no corresponding genes in the UniProt database. We annotated/curated 592 genes from these transcripts, among which 202 were novel while 390 were improvements of existing genes in the G. m. morsitans genome. Among the novel genes, 94 had orthologs in D. melanogaster, M. domestica or An. gambiae while 88 had homologs in UniProt. These orthologs were putatively associated with oxidative regulation, protein synthesis, transcriptional and/or translational regulation, detoxification and metal ion binding, thus providing insight into their specific roles in antennal physiological processes in male G. m. morsitans. A novel gene (GMOY014237.R1396) was differentially expressed in response to the attractant. We thus established significant gaps in G. m. morsitans genome annotation and identified novel male antennae-expressed genes in the genome, among which > 53% (108) are potentially G. m. morsitans specific.
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    A Classification Model for Water Quality analysis Using Decision Tree
    (2019-06) Gakii, Consolata; Jepkoech, Jennifer
    A classification algorithm is used to assign predefined classes to test instances for evaluation) or future instances to an application). This study presents a Classification model using decision tree for the purpose of analyzing water quality data from different counties in Kenya. The water quality is very important in ensuring citizens get to drink clean water. Application of decision tree as a data mining method to predict clean water based on the water quality parameters can ease the work of the laboratory technologist by predicting which water samples should proceed to the next step of analysis. The secondary data from Kenya Water institute was used for creation of this model. The data model was implemented in WEKA software. Classification using decision tree was applied to classify /predict the clean and not clean water. The analysis of water Alkalinity,pH level and conductivity can play a major role in assessing water quality. Five decision tree classifiers which are J48, LMT, Random forest, Hoeffding tree and Decision Stump were used to build the model and the accuracy compared. J48 decision tree had the highest accuracy of 94% with Decision Stump having the lowest accuracy of 83%.
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    Information Technology In Government Services Delivery: A Case Study Of Huduma Center Kenya
    (2018-12) Gakii, Consolata; Mukiri, Victoria F.; Murimi, Maurice
    The Huduma Kenya program was developed by the Kenyan government with an aim of using technology to improve the service delivery to the citizens. The Program uses many channels to meet different and varied needs of the citizens by having a one stop shop environment. The main objective of this paper is to examine a successful information technology project in Kenya that has changed the government service delivery due to the advancement in technology. The case study in this paper is Huduma Kenya program, under which the Government of Kenya has advanced citizencentered public service delivery through a variety of channels, including deploying digital technology and establishing citizen service centers across the country. The project was initiated by Kenyan government who are also the main sponsors since 2013. The success of this project can be attributed to the use of existing infrastructure in Post offices of Kenya and the support from the Kenyan government. Information communication technology (ICT) enabled communication between centers and the Secretariat, automated data collection and closed-circuit television monitoring, are major contributors to Huduma Kenya‘s positioning as an antithesis to inefficiency and corruption.
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    Staff Profile:Dr.Consolata Gakii Mwirichia
    (University of Embu, 2020-01) Gakii, Consolata
    Dr. Consolata Gakii holds a PhD, an MSC, and a Bachelor of Science in Information Technology from Jomo Kenyatta University of Agriculture and Technology, Kenya. Consolata is a machine learning and big data analytics expert. She is driven by the opportunity to make a significant impact in an increasingly data-driven world by applying skills and expertise to tackle complex problems and extract actionable insights from one health related data. Presently, she is actively engaged in projects spanning Embu and Murang’a counties, employing artificial intelligence to raise awareness about HIV/AIDS, exemplifying her commitment to harnessing technology for public health initiatives.Research Interests. Her research interest is to apply machine learning and data mining techniques to discover knowledge from complex and large-scale data sets.
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    TELECOMMUTING MODEL FOR SMALL AND MEDIUM ENTERPRISES (SMES) IN KENYA
    (2016-07) Gakii, Consolata; Mwangi, Waweru; Okeyo, George
    The aim of this study was to use adaptive structuration theory as a tool to come up with Telecommuting model that can be adopted by SMEs in Kenya. A survey was done to understand the extent of telecommuting and the available technological tools in the Kenyan SMEs. Data from this survey indicates that most of the workers have reliable and fast internet access away from the office and reliable information support team. These employees also reported improvement in quality and efficiency in terms of service delivery. This was attributed to the time available to concentrate on their tasks unlike in the office where there could be interruptions or meetings. A representative microfinance was chosen to understand the organizational structure and the information technology infrastructure available in a typical Kenyan SME. Results showed that the SME had both the IT infrastructure and personnel in place. Based on these findings, an AST derived model was developed and tested. Our study shows that adoption of the developed AST derived telecommuting model could lead to increased productivity, efficiency and quality of work. Findings from this study would assist stakeholders use the available infrastructure and personnel to allow formal telecommuting.