HBCU-UP-TIP Summer 2014 Research Program in Biomathematics and Bioinformatics

2014-Summer Research Participants
Front (L to R): Dr. Lei Qian, Shayla Nolen, Quinetra Gathers, Quzonna Reed, Elisha Hall and Dr. Brian Nelms.
Back (L to R): Roquibat Giwa, Dr. Sanjukta Hota, Dr. Justice Ike, Favour N Esedebe, Oreoluwa Onabolu, Sultan Yagboyaju, Whitney Howard, and Brandon Williams

2014-Summer Research Participants

Abstracts of Summer Research Projects:

 

1. Amino Acid Sequence Comparison to Uncover Functions of the C-Terminal Portion of FKH-8

Quzonna Reed
Quzonna Reed

Advisor: Dr. Brian Nelms, Department of Biology, Fisk University.

Abstract:

Forkhead-8 (FKH-8) is a winged helix transcription factor protein important for dopaminergic neuron function in C. elegans, a transparent nematode we are using as a model system.  Most sequence comparisons examine only the winged helix DNA binding domain, but we wanted to determine if sequence comparisons of the C-terminal portion of the protein could give insight into additional molecular functions.  We have found that 3 portions of the C-terminus are relatively conserved in other nematodes, bacteria, and some plants. Our findings suggest that the C-terminus of FKH-8 may have something in common with enzymes that catalyze the phosphorylation of other residues such as serine, threonine, inosine monophosphate, and aspartic acid. Our next steps will include using protein structure prediction tools to predict the shape of the C-terminal portion of FKH-8, and learn more about its function (as structure is related to function).

2. Analyzing the Forkhead-8 protein sequence in C. elegans to find the overall function of the protein

Quinetra Gathers

Advisor: Dr. Brian Nelms, Department of Biology, Fisk University.

Abstract:

The neurotransmitter dopamine is used for many processes in the brain such as motor control, cognition, and mood or behavior.  It is an important factor in many diseases such as Parkinson’s Disease, Attention-deficit/hyperactivity disorder, and Schizophrenia.  We are using Caenorhabditis elegans (C. elegans), a roundworm commonly used for research, as a model system to study these neurons.  C.elegans can be easily grown on petri dishes in large quantities making them very cost-effective.  C.elegans are also transparent, making them easy to study because all of the cells including neurons are visible under a microscope.  Importantly, the molecules used in C. elegans are often very similar to those in humans.  Previous work in the Nelms lab has shown that a forkhead family transcription factor, FKH-8, is essential for the regulation of dopaminergic functions.  We would like to understand more about the function of this protein.  Although a highly conserved winged helix domain has been identified, the function of the N-terminal and C-terminal regions has yet to be discovered.  I compared the N-terminal of the forkhead-8 protein to other organisms to see if it aligned with their amino acid sequence to give insight into the function of the N-terminal.  Unfortunately, this analysis strategy has not given us any new insights so far.

3. Qualitative Analysis of the Lotka-Volterra Type Competition Model

Whitney D. Howard
Whitney D. Howard

Advisor: Dr. Sanjukta Hota, Department of Mathematics and Computer Science, Fisk University.

Abstract:

The Lotka-Volterra system of equations is used to analyze the interactive population models. It is named after American mathematical biologist Alfred J. Lotka (1880-1949) and Italian mathematician Vito Volterra (1860-1940). This project focuses on analyzing the continuous dynamic Lotka-Volterra competition model numerically and qualitatively and applications to various cases. This was done by performing sensitivity analysis of the initial conditions and stability analysis of the equilibrium points in each case. Numerical computation and simulation is performed using Mathematica. Result shows that the initial conditions play an important role in determining the long term population size of the species in each case. Three different types of behavior were mainly observed: 1) one of the species will eventually become instinct, 2) both of the species will maintain a balance, or 3) the populations of the species will be periodic.

4. A discrete dynamic model of oxygen absorption with different breathing patterns

Oreoluwa Onabolu
Oreoluwa Onabolu

Advisor:  Dr. Sanjukta Hota, Department of Mathematics and Computer Science, Fisk University.

Abstract:

Breathing is a process that is fundamental to the survival of the living species on earth. Different living organisms have their means of achieving their physiological respiration. In human beings, the two lungs are the major organs responsible for this vital process. In this project, a mathematical model is developed in discrete dynamical systems to analyze the mechanism of oxygen absorption in the human body.

I determine quantitatively, supported by numerical simulation through Mathematica, the chemical concentration of a particular substance in the body after each breath. I have also investigated on how the dynamics of the model is affected by several factors, such as, variations in the chemical concentrations of the substance in the outside air, fraction of air exchanged, quantity of oxygen absorbed into the blood and different breathing patterns. Mathematical expression was derived in each case supported by graphical representation.

5. An Investigative study of HIV/AIDS among African Americans and development of a Mathematical Model with Stability Analysis

Shayla NolenShayla Nolen

Advisor:  Dr. Sanjukta  Hota, Department of Mathematics and Computer Science, Fisk University.

Abstract:

HIV/AIDS has become the biggest epidemic since the Black Plague over five hundred years ago. Within about thirty years into the HIV/AIDS epidemic, close to forty million people have been affected worldwide and the number is alarmingly large within the African American population in the United States.

My goal for this research was to analyze mathematically the progression and transmission dynamics of the HIV epidemic and to perform stability analysis for the epidemic. A three compartment  model of HIV/AIDS was developed based on the SIR epidemic model with the assumption that the recruitment rate to the susceptible group is proportional to the size of the susceptible population. Both equilibrium points, such as, the disease free equilibrium point (DFE) and the endemic equilibrium point (EE) were found and the asymptotic stability at the equilibrium points was determined. Conditions were derived for the system to be stable, unstable or saddle at these equilibrium points, and the numerical simulations were performed to illustrate the analytical results.

The result shows that the recruitment rate plays an important role in the stability analysis around both the equilibrium points, DFE and EE.  In particular, endemic equilibrium point was found to be stable if the recruitment rate is greater than the natural death rate but less than the infection rate.

6. A Quantitative Analysis of SIR-type Malaria Models

Elisha HallElisha Hall

Advisor:  Dr. Sanjukta Hota, Department of Mathematics and Computer Science, Fisk University.

Abstract:

Malaria is a parasitic infection transmitted by female Anopheles mosquitos which can be fatal if not treated. The CDC reports Malaria had killed more than 627,000 people and created 207 million clinical episodes in 2012 alone. With approximately 1,500-2,000 cases reported every year, America is far from being isolated from this disease.

Sir Ronald Ross was the first to create an analytical model of Malaria and received a Nobel Prize for his work in 1902. Others such as Macdonald and Lotka have built upon this basis to give a refined view of the behavior of Malaria and treatment options. Ross’ model, a general Kermack-McKendrick SIR-type model, is still being used as a basis to create further models of the Malaria epidemic.

This project is a comprehensive analysis of Ross and Ross-Lotka models including determining the equilibrium points, reproduction numbers and stability of the equilibrium point. Further study is done to compare/contrast both models.

7. Fkh-8 Genomic Sequence Analysis

Giwa RoquibatGiwa Roquibat

Advisor: Dr. Brian Nelms, Department of Biology, Fisk University.

Abstract:

Dopaminergic neurons of the midbrain are the main source of dopamine (DA) in the mammalian central nervous system. Their loss is associated with one of the most prominent human neurological disorders, Parkinson's disease (PD). Dopaminergic neurons play an important role in the control of multiple brain functions including voluntary movement and a broad array of behavioral processes such as mood, addiction, and stress. The nematode roundworm, C.elegans, is a model organism because it is genetically tractable, has a short life span, a well-defined nervous system and is transparent; thus the nervous system, can be easily examined. FKH-8 gene is highly expressed in dopamine neurons and crucial to the development and differentiation of these neurons. Studying the FKH-8 gene provides a better understanding of the molecules needed for DA signaling. Comparisons of the FKH-8 genes of C.elegans, C. brenneri, C.briggsae, C.remanei, and C.japonica were made in order to determine regions of highly conserved domains. The intronic CNS was run in JASPAR to determine the C.elegans protein homolog. I am currently studying these genes to see if they have any dopamine related function and if their mutations could lead to neurological diseases in humans.

8. Developing Effective Algorithms For Biological Data Access and Sequence Analysis of C-Elegans

Sultan YagboyajuSultan Yagboyaju

Advisor: Dr. Lei Qian, Department of Mathematics and Computer Science, Fisk University.

Abstract:

Real time access to biological data and information has become increasingly important in the modern day world. Biological data has helped improve the quality of research, the standard of medical care and also the production of drugs and vaccines. Many biological databases such as Wormbase and NCBI have been built to allow access through web browsers however using web browsers may be difficult and inefficient especially when we have to synthesize data from multiple sources or we have to do batch queries .In this project, We will be using Python to develop a tool to simulate a web search and automatically parse the web pages to extract data, analyze data and generate required primers. The ultimate goal of this project will be to develop web services and applications to seamlessly access and analyze data from biological databases.


9. Using Machine Learning Techniques to Predict the Secondary Structure of Protein

Brandon WilliamsBrandon Williams

Advisor: Dr. Lei Qian, Department of Mathematics and Computer Science, Fisk University.

Abstract:

It is from the structure of the protein, that scientists are able to gain an understanding of protein function and its role in the body. In this project, we focused on using artificial neural networks, a pattern recognition technique, to predict the secondary structures of proteins. Our goal was to investigate different neural network architectures to determine the best configuration for predicting the secondary structures of proteins from their primary sequences. We also investigated different techniques to run neural network in computers with low memory. Using the proteins dataset from the CullPDB database, we tested different neural network architectures in a computer cluster and also developed algorithms to train the network in our own personal computers with less memory. Their performances are compared.