Ebinformatics: Ebola fuzzy informatics systems on the diagnosis, prediction and recommendation of appropriate treatments for Ebola virus disease (EVD)

AbstractEbola Virus Disease (EVD) also known as the Ebola hemorrhagic fever is a very deadly infectious disease to humankind. Therefore, a safer and complementary method of diagnosis is to employ the use of an expert system in order to initiate a platform for pre-clinical treatments, thus acting as a precursor to comprehensive medical diagnosis and treatments. This work presents a design and implementation of informatics software and a knowledge-based expert system for the diagnosis, and provision of recommendations on the appropriate type of recommended treatment to the Ebola Virus Disease (EVD).In this research an Ebola fuzzy informatics system was developed for the purpose of diagnosing and providing useful recommendations to the management of the EVD in West Africa and other affected regions of the world. It also acts as a supplementary resource in providing medical advice to individuals in Ebola – ravaged countries. This aim was achieved through the following objectives: (i) gathering of facts through the conduct of a comprehensive continental survey to determine the knowledge and perception level of the public about factors responsible for the transmission of the Ebola Virus Disease (ii) develop an informatics software based on information collated from health institutions on basic diagnosis of the Ebola Virus Disease-related symptoms (iii) adopting and marrying the knowledge of fuzzy logic and expert systems in developing the informatics software. Necessary requirements were collated from the review of existing expert systems, consultation of journals and articles, and internet sources. Online survey was conducted to determine the level at which individuals are aware of the factors responsible for the transmission of the Ebola Virus Disease (EVD). The expert system developed, was designed to use fuzzy logic as its inference mechanism along with a set of rules. A knowledge base was created to help provide diagnosis on the Ebola Virus Disease (EVD). The Root Sum Square (RSS) was adopted as a fuzzy inference method. The degree of participation of each input parameter was shown using the triangular membership function and the defuzzification technique used is the Center of Gravity (CoG).The resulting software produced a user-friendly desktop-based, Windows-based, application and the tools used were explained in the results section in three (3) separate phases. First, a comprehensive online survey was conducted over a period of about 3–9 months. 100 Participants participated in the survey on the perception and knowledge analysis of different individuals about Ebola Virus Disease (EVD) transmission factors. 31% of the participants didn't know that there is presently no cure for Ebola. 28% believed that there is presently a cure for Ebola. 43% agreed that Ebola is both air-borne and water-borne, while 33% disagreed, 24% do not know. 23% believed that insects and mosquitoes can help in transmitting the Ebola Virus Disease (EVD), while 30% were completely ignorant. We noticed that ignorance was a major limiting factor among some participants.Second, a test was conducted among 45 people. Results from a comprehensive testing of the Ebinformatics software by allowing users to operate and use the software, revealed that 60% of them were satisfied, while 16% were not satisfied with the software, while 24% were indifferent. 69% of the users were in agreement that Ebinformatics was supportive, 20% disagreed, while 11% were indifferent. 67% found the software easy to use, 13% disagreed, while 20% were indifferent. Third, the output of the software, showing the various diagnosis and recommendations interfaces were presented. Recommendations were also given with respect to how the system can be extended, and further improved upon

Development of a Secured Information System to Manage Malaria Related Cases in South Western region of Nigeria

Abstract Effective community based management of malaria incidences in most community health care centers are hampered by failure in the prompt diagnosis and treatment of malaria. This challenge is exacerbated by the emergence of multidrug resistant plasmodium parasites which makes ineffective most of the effective therapeutic drugs used in the treatment of malaria. Furthermore, even at abrupt changes in the therapeutic recommendations does not always translate to an immediate change in the effective management and control of malaria. Thus, the quest for effective diagnosis and appropriate treatment becomes a daunting and necessary task. . In this article, a secured Information system to manage malaria related cases was developed by 2-tier architecture by using the VB.NET programming language within the Microsoft Visual studio 2008 edition. The database employed for storing relevant data was the SQL server 2005 edition and fingerprint device integrated into the information system was the Microsoft fingerprint reader. From the results in this study, we modeled a feasible medical history system for prompt diagnosis, effective drug recommendations and promulgation of policies that would serve as palliatives for community health care centers that suffers shortages in material and human resources handling malaria and its related diseases

Paving the Way Towards a Successful and Fulfilling Career in Computational Biology

Most of us will spend a significant amount of time and effort throughout our lives in improving our career. The decisions we make shape how our career progresses, and the right decisions can ensure it is successful and fulfilling. Early decisions can have a strong influence, especially in today’s competitive job market, where a university degree will not guarantee the best job. It is vital these early decisions are well informed and based on access to as much information as possible. As part of an effort to ensure that computational biologists and students are guided into the right career paths, the Regional Student Group (RSG) program, an arm of the International Society for Computational Biology (ISCB), has provided a range of activities to assist computational biologists and bioinformatics researchers in their career development. These include organizing prac�tical workshops and seminars presented by leading experts on how to broaden the scope of career options and guarantee success. This article provides insight on some of these activities and highlights the benefits gained through the shared experiences of RSGs in running career-related activities

Computational Biology and Bioinformatics in Nigeria

Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in the biological data generated by the scientific community. The critical need to process and analyze such a deluge of data and turn it into useful knowledge has caused bioinformatics to gain prominence and importance. Bioinformatics is an interdisciplinary research area that applies techniques, methodologies, and tools in computer and information science to solve biological problems. In Nigeria, bioinformatics has recently played a vital role in the advancement of biological sciences. As a developing country, the importance of bioinformatics is rapidly gaining acceptance, and bioinformatics groups comprised of biologists, computer scientists, and computer engineers are being constituted at Nigerian universities and research institutes. In this article, we present an overview of bioinformatics education and research in Nigeria. We also discuss professional societies and academic and research institutions that play central roles in advancing the discipline in Nigeria. Finally, we propose strategies that can bolster bioinformatics education and support from policy makers in Nigeria, with potential positive implications for other developing countries. © 2014 Fatumo et al.SAF was supported by H3ABioNet NABDA Node, Abuja, Nigeria with NIH Common Fund Award/NHGRI Grant Number U41HG006941 and Genetic Epidemiology Group at Wellcome Trust Sanger Institute.Published versio

An in-silico analysis of OGT gene association with diabetes mellitus

O-GlcNAcylation is a nutrient-sensing post-translational modification process. This cycling process involves two primary proteins: the O-linked N-acetylglucosamine transferase (OGT) catalysing the addition, and the glycoside hydrolase OGA (O-GlcNAcase) catalysing the removal of the O-GlCNAc moiety on nucleocytoplasmic proteins. This process is necessary for various critical cellular functions. The O-linked N-acetylglucosamine transferase (OGT) gene produces the OGT protein. Several studies have shown the overexpression of this protein to have biological implications in metabolic diseases like cancer and diabetes mellitus (DM). This study retrieved 159 SNPs with clinical significance from the SNPs database. We probed the functional effects, stability profile, and evolutionary conservation of these to determine their fit for this research. We then identified 7 SNPs (G103R, N196K, Y228H, R250C, G341V, L367F, and C845S) with predicted deleterious effects across the four tools used (PhD-SNPs, SNPs&Go, PROVEAN, and PolyPhen2). Proceeding with this, we used ROBETTA, a homology modelling tool, to model the proteins with these point mutations and carried out a structural bioinformatics method– molecular docking– using the Glide model of the Schrodinger Maestro suite. We used a previously reported inhibitor of OGT, OSMI-1, as the ligand for these mutated protein models. As a result, very good binding affinities and interactions were observed between this ligand and the active site residues within 4Å of OGT. We conclude that these mutation points may be used for further downstream analysis as drug targets for treating diabetes mellitus

Molecular Dynamic Simulation Reveals Structure Differences in APOL1 Variants and Implication in Pathogenesis of Chronic Kidney Disease.

BACKGROUND: According to observational studies, two polymorphisms in the apolipoprotein L1 (APOL1) gene have been linked to an increased risk of chronic kidney disease (CKD) in Africans. One polymorphism involves the substitution of two amino-acid residues (S342G and I384M; known as G1), while the other involves the deletion of two amino-acid residues in a row (N388 and Y389; termed G2). Despite the strong link between APOL1 polymorphisms and kidney disease, the molecular mechanisms via which these APOL1 mutations influence the onset and progression of CKD remain unknown. METHODS: To predict the active site and allosteric site on the APOL1 protein, we used the Computed Atlas of Surface Topography of Proteins (CASTp) and the Protein Allosteric Sites Server (PASSer). Using an extended molecular dynamics simulation, we investigated the characteristic structural perturbations in the 3D structures of APOL1 variants. RESULTS: According to CASTp's active site characterization, the topmost predicted site had a surface area of 964.892 Å2 and a pocket volume of 900.792 Å3. For the top three allosteric pockets, the allostery probability was 52.44%, 46.30%, and 38.50%, respectively. The systems reached equilibrium in about 125 ns. From 0-100 ns, there was also significant structural instability. When compared to G1 and G2, the wildtype protein (G0) had overall high stability throughout the simulation. The root-mean-square fluctuation (RMSF) of wildtype and variant protein backbone Cα fluctuations revealed that the Cα of the variants had a large structural fluctuation when compared to the wildtype. CONCLUSION: Using a combination of different computational techniques, we identified binding sites within the APOL1 protein that could be an attractive site for potential inhibitors of APOL1. Furthermore, the G1 and G2 mutations reduced the structural stability of APOL1

Bioinformatics, Computational Informatics, and Modeling Approaches to the Design of mRNA COVID-19 Vaccine Candidates.

This article is devoted to applying bioinformatics and immunoinformatics approaches for the development of a multi-epitope mRNA vaccine against the spike glycoproteins of circulating SARS-CoV-2 variants in selected African countries. The study’s relevance is dictated by the fact that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) began its global threat at the end of 2019 and since then has had a devastating impact on the whole world. Measures to reduce threats from the pandemic include social restrictions, restrictions on international travel, and vaccine development. In most cases, vaccine development depends on the spike glycoprotein, which serves as a medium for its entry into host cells. Although several variants of SARS-CoV-2 have emerged from mutations crossing continental boundaries, about 6000 delta variants have been reported along the coast of more than 20 countries in Africa, with South Africa accounting for the highest percentage. This also applies to the omicron variant of the SARS-CoV-2 virus in South Africa. The authors suggest that bioinformatics and immunoinformatics approaches be used to develop a multi-epitope mRNA vaccine against the spike glycoproteins of circulating SARS-CoV-2 variants in selected African countries. Various immunoinformatics tools have been used to predict T- and B-lymphocyte epitopes. The epitopes were further subjected to multiple evaluations to select epitopes that could elicit a sustained immunological response. The candidate vaccine consisted of seven epitopes, a highly immunogenic adjuvant, an MHC I-targeting domain (MITD), a signal peptide, and linkers. The molecular weight (MW) was predicted to be 223.1 kDa, well above the acceptable threshold of 110 kDa on an excellent vaccine candidate. In addition, the results showed that the candidate vaccine was antigenic, non-allergenic, non-toxic, thermostable, and hydrophilic. The vaccine candidate has good population coverage, with the highest range in East Africa (80.44%) followed by South Africa (77.23%). West Africa and North Africa have 76.65% and 76.13%, respectively, while Central Africa (75.64%) has minimal coverage. Among seven epitopes, no mutations were observed in 100 randomly selected SARS-CoV-2 spike glycoproteins in the study area. Evaluation of the secondary structure of the vaccine constructs revealed a stabilized structure showing 36.44% alpha-helices, 20.45% drawn filaments, and 33.38% random helices. Molecular docking of the TLR4 vaccine showed that the simulated vaccine has a high binding affinity for TLR-4, reflecting its ability to stimulate the innate and adaptive immune response

Android Mobile Informatics Application for some Hereditary Diseases and Disorders (AMAHD): A complementary framework for medical practitioners and patients

Hereditary diseases and disorders constitute a public health problem. Many people in rural communities of developing countries of the world are particularly ignorant about the cause, modes of transmissions and the treatment plans for such diseases. In some cases, some people lack essential knowledge between common and rare hereditary diseases.It is therefore appropriate and essential to develop a mobile application that will act as an educative resource and a good knowledge base for common and rare hereditary diseases.The aim of this research is to develop AMAHD (Android Mobile Informatics Application for some Hereditary Diseases and Disorders).The objectives of this research are to create an android mobile application that will act as a reference point and provide useful information about various hereditary diseases to medical personnel and professionals; provide additional educational resource to biological and bioinformatics researchers in different higher institutions; and provide a pedagogical, diagnostic and complementary foundational learning tool for African research students in biosciences, bioinformatics, and all other categories of students that currently engage in multidisciplinary research in the aspect of hereditary diseases.Essential data was sourced from relevant literature. We developed AMAHD through an integration of programming languages in Java and XML (Extended Markup Language). SQLite was used to implement the database. We developed a Logical Disjunction Rule-based Algorithm (LDRA) for the AMAHDâs diagnosis module.A comparative analysis between existing commercial hereditary mobile applications and AMAHD was conducted and the results presented. A world-wide online survey (spanning Africa, Asia, Europe, America and Australia) was conducted to sample the opinion of individuals across the globe on the classification of hereditary diseases as either rare or common, within their respective regions. In addition, an evaluation of AMAHD on the offline platform was conducted by administering paper questionnaires and asking users direct questions about how they respectively rate the performance of AMAHD based on certain evaluation criteria. Furthermore, a separate evaluation of AMAHD was conducted using online survey monkey. Finally, a comparative analysis between the results obtained from the online evaluation and offline evaluation of AMAHD was conducted and presented.The results of the surveymonkey online questionnaire revealed that: 58.49% of the participants agreed that AMAHD can be used to diagnose users ailments based on the hereditary disease symptoms they supplied to the mobile application; 13.21% disagreed, while 28.30% of the participants were indifferent. 71.7% of the participants agreed that AMAHD can act as a complementary resource for supplementary healthcare support; 5.66% disagreed, while 22.64% of the participants were indifferent. 88.46% of the participants agreed that AMAHD can be particularly supportive to developing countries where there is less awareness of the deadly effects on hereditary diseases; 1.92% disagreed, while 9.62% were indifferent. Finally, 86.79% of the participants agreed that AMAHD can be useful as an android health application, 13.21% disagreed. Keywords: Hereditary diseases, Android application, Medical practitioners, Informatics, Bioinformatics, Mobile informatic

Reducing Road-Traffic Accidents on African Roads through a Computer Simulation Programming Approach

Abstract: The mortality rate in the West African sub-region of the world is undoubtedly very high. In Africa for example, the prevalent incidences of road-traffic accidents has been responsible for the untimely death of many innocent citizens. Also, particularly disturbing is the high number of sudden deaths scenarios that are recorded yearly among patients on an emergency transfer held up within terrible road-traffic congestions. Although this particular road-accident phenomenon is not just limited to West African Countries, it is particularly disturbing that Africa seems to be among the few remaining regions of the world where a permanent antidote or a solution approach is yet to be found and adequately implemented for the full benefits of the victims of such unpleasant circumstances. Within the Lagos metropolis in Nigeria, for example, many lives have been lost as a result of roadtraffic accidents. As a result of this, there is the need to reduce the numbers of deaths of innocent citizens on West African highways through a simulated programming approach which will ultimately help to adequately cater for the security, safety and welfare of the African people and also reduce the mortality rate within the African continent. Thus, in this research work, a simulated programming approach will be applied to reducing road-traffic accidents on West African high-ways

Malavefes: A computational voice-enabled malaria fuzzy informatics software for correct dosage prescription of anti-malarial drugs

Malaria is one of the infectious diseases consistently inherent in many Sub-Sahara African countries. Among the issues of concern are the consequences of wrong diagnosis and dosage administration of anti-malarial drugs on sick patients; these have resulted into various degrees of complications ranging from severe headaches, stomach and body discomfort, blurred vision, dizziness, hallucinations, and in extreme cases, death. Many expert systems have been developed to support different infectious disease diagnoses, but not sure of any yet, that have been specifically designed as a voice-based application to diagnose and translate malaria patients’ symptomatic data for pre-laboratory screening and correct prescription of proper dosage of the appropriate medication. We developed Malavefes, (a malaria voice-enabled computational fuzzy expert system for correct dosage prescription of anti-malarial drugs) using Visual Basic.NET., and Java programming languages. Data collation for this research was conducted by survey from existing literature and interview from public health experts. The database for this malaria drug informatics system was implemented using Microsoft Access. The Root Sum Square (RSS) was implemented as the inference engine of Malavefes to make inferences from rules, while Centre of Gravity (CoG) was implemented as the defuzzification engine. The drug recommendation module was voice-enabled. Additional anti-malaria drug expiration validation software was developed using Java programming language. We conducted a user-evaluation of the performance and user-experience of the Malavefes software. Keywords: Informatics, Bioinformatics, Fuzzy, Anti-malaria, Voice computing, Dosage prescriptio