Repository logo
  • English
  • Català
  • Čeština
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • Latviešu
  • Magyar
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Suomi
  • Svenska
  • Türkçe
  • Қазақ
  • বাংলা
  • हिंदी
  • Ελληνικά
  • Yкраї́нська
  • Log In
    New user? Click here to register.Have you forgotten your password?
Repository logo
  • Communities & Collections
  • All of DSpace
  • English
  • Català
  • Čeština
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • Latviešu
  • Magyar
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Suomi
  • Svenska
  • Türkçe
  • Қазақ
  • বাংলা
  • हिंदी
  • Ελληνικά
  • Yкраї́нська
  • Log In
    New user? Click here to register.Have you forgotten your password?
  1. Home
  2. Browse by Author

Browsing by Author "Olorede, K. O."

Now showing 1 - 3 of 3
Results Per Page
Sort Options
  • Loading...
    Thumbnail Image
    Item
    Genetic Diagnosis, Classification, and Risk Prediction in Cancer Using Next-Generation Sequencing in Oncology
    (CRC Press, Taylor & Francis Grou, 2024) Dauda, K. A.; Olorede, K. O.; Banjoko, A. W.; Yahya, W. B.; Ayipo, Y. O.
    In recent years, researchers have been overwhelmed with large-scale genomic data due to an advancement toward data-driven science called next-generation sequencing. Hence, it has been established that if the sequence of a gene is mutated, there is the possibility of unscheduled production of the protein, leading to cancer. The prediction of genes and variants into true and false pathogenic groups, extraction of the most influential genes, and identification of a pattern from this genomic data are of interest to biologists and medical professionals. However, the identification and extraction of these biomarkers and molecular signatures of different cancers among thousands of genes seem complex and problematic. Therefore, this chapter is aimed to develop an algorithm that can aid and provide efficient solutions for gene extraction, identification, and prediction in the realm of next-generation sequencing data. The proposed algorithm consists of three folds: the filtering fold using minimum redundancy maximum relevance (MRMR), the wrapper fold using the Boruta algorithm, and the last fold consisting of the use of deep learning (DL). A comparison assessment was performed on the proposed algorithm and the existing methods using five RNA-seq datasets from a cancer patient. The results revealed that the proposed algorithm significantly outperforms the existing methods in selecting fewer highly relevant genes for the cancer type while maintaining a high classification prediction accuracy.
  • Loading...
    Thumbnail Image
    Item
    On the Approximation of Pareto Distribution to Exponential Distribution Using the Gini Coefficient of Inequality
    (Professional Statisticians Society of Nigeria (PSSN), 2017) Yahya W.B.; Garba M. K.; Amidu L; Olorede, K. O.; Gatta, N. F.; Amusa L. B.
    Pareto proposed that income and wealth distribution obeys a universal power law valid for all times and countries, but subsequent studies have often disputed this position. Some even argued there is indeed no Pareto Law and that it should be entirely discarded in studies on distribution of wealth or resources. Many other probability distributions have been proposed such as log normal, exponential, gamma and two other forms by Pareto himself. Using data on imported goods from the National Bureau of Statistics as a case of distribution of wealth in Nigeria, we demonstrated that the distribution of money spent on importation in Nigeria also follow exponential distribution using the Gini coefficient which is a measure of inequality (degree of concentration) of a variable in the distribution of resources. Simulation studies were carried out at different sizes of items (or households) and varying values of the shape parameter and we compare how close the Gini coefficients of the exponential distribution approximate those obtained from the Pareto data as a credible alternative to Pareto distribution.
  • Loading...
    Thumbnail Image
    Item
    Peace and Conflict Management in Nigeria: Mapping the Historical Role of Language in Peace Journalism in the 21st Century
    (International Institute of Science and Technology (IISTE), 2015) Olorede, S. O.; Olorede, K. O.
    This paper examines the roles of language usage in peace and conflict management in Nigeria. It exposes the influence of language in mass media reporting by journalism in the 21st century. It traces the past and interprets the present based on the experience of the past to forecast the likely trend of event in future. Relevance instances of language communication bypass were among those factors examined by this paper to understand the effect of such on the peace and conflict restoration in the environment. Stages of conflict in Nigeria and how media portray conflict stories through language selection and usage in their reporting were identified. A chronicle of recent conflicts in Nigeria was explored to drive home every point made in this paper. Suggestions were also made on how best conflict could be covered to sustain peace and prevent conflict in Nigeria. It is therefore hoped that this paper would contribute immensely to peace and conflict management in this millennium and beyond.

KWASU Library Services © 2023, All Right Reserved

  • Cookie settings
  • Send Feedback
  • with ❤ from dspace.ng