The Mercer Science and Engineering fair asks for answering some questions regarding the research procedures and the project importance. They are good questions to help people reflect deeply on what we had done. I am posting them here to share with everyone.
- What was the major objective of your project and what was your plan to achieve it?
In the project, my work is based on the genome of the SARS-COV-2 virus which caused the COVID-19 pandemic last year. The major objective was to predict the genome mutation patterns using computational modeling. I expected the modeling would show us different patterns in different geographical regions and which sites could be the most important in affecting the mutation of the virus. The prediction might provide an alternative reference for other research and vaccine applications.
In the spread of COVID-19, the mutation of the SARS-COV-2 virus has been found, and scientists imply that the mutation may affect the spread of the virus. So, I planned to predict the mutation and find out the characteristics of the mutation, and then develop a website to show the predicted results in real-time.
To achieve this, my plan was as follows, as written in my research plan:
- Collect virus sequence data from the open-source database.
- Categorize the sequence mutation based on sampling locations as some reports indicated the mutation was regional.
- To predict the mutation trend, organize the data into time series, calculate mutation frequencies and disregard the low-frequency sites.
- Fit the data with the ARIMA model (a statistical model I used before) for prediction.
- Assess whether the mutations would cause amino acid changes or not.
- At last, build a website for others to access my prediction results and display the mutation trend in real-time automatically. a. Was that goal the result of any specific situation, experience, or problem you encountered?
After the COVID-19 pandemic breakout in the US, the schools, including mine, had to close. During that time, I had to stay home and took online classes, and I checked the case counts hoping for the end of the disease. At school, I have interests in computer sciences, so I learned a lot of knowledge on building models using computer science, then I tried to build a model for predicting the cases of COVID-19. My mathematical supervisor introduced the ARIMA model to me and I found the model is working very well in predicting the cases of COVID-19 which is data with time series. After that, I started to think about what other predictions I could do. From the news, I learned that the virus had been continuing to mutate. Experts said that its pathogenicity and transmission are constantly changing with the mutation. Because most vaccines are using a special site on the virus genome to detect and bind with the protein to inhibit the activity of the virus, the mutations may affect the development of the vaccine and sometimes make the vaccine ineffective. And this gave me an idea that I can use my computer science and math skills to model the mutation rate for every genome site, and this would give me a mutation trend of the COVID-19 virus. And if I use the ARIMA model which I’ve learned from predicting cases on predicting the mutation rate of important sites for COVID-19, It can show different patterns of virus mutation in different countries. Such predictions might help scientists evaluate the tendency of mutation for each site, which could help them estimate the effectiveness of the vaccine in the long term and the possibility of using one vaccine which develops in one region in another region. b. Were you trying to solve a problem, answer a question, or test a hypothesis?
I was trying to solve a problem that there’s no specific evaluation model on the possibility of mutation. Of course, it is based on a hypothesis that the virus mutation is predictable.
- What were the major tasks you had to perform in order to complete your project?
Prior to the prediction:
Before the prediction, data acquisition and data cleaning were very important and heavy.
I had to compare and collect a sufficiently large amount of data from many different open-source websites to build a credible, accurate, and real-time database. I had to filter through all the data to make sure they contained necessary information without pre-processing.
Communication was also very important, without sufficient communication, some problems may occur after you finish everything, and you may have to redo the entire thing.
The first time when I obtained data from the CNCB database, the administration of the database suggests me to collect data from a special portal, it can give me every mutation data and the information of sequence in one file. Although the data had a special format inconsistent with data from other sources, I still spend a whole week understanding the format and building programs to extract information that I think is useful.
However, after I use my code to format the data into what we can read, I found that the data have already been pre-processed, that all the back mutations were removed. But, the back mutation information was VERY important for my analysis, so I had to ask the administrator to point me to other data sources to restore the back mutation. And after he gives me the new data, I have to redo the entire thing to reformat the data again to what I can read and use.
Prediction:
After collecting data and translate it to what we can use, I can finally start my prediction
Categorize data based on location. This is an important step but relatively easy to do. We classified those data according to continents because previous works showed the possibility of different trends in different continents.
Organize data into time series and calculate the mutation frequency.
Fit the data using the ARIMA model to obtain predictions. Because I should predict every single site separately, editing model parameters by hands would not be humanly possible. So, I designed an automatic parameter selection flow according to the ARIMA model and spent time building a program to automatically evaluate the parameters. For some predictions, data should also be truncated to remove the interference from low sampling numbers due to early reports (if a single new data will cause a more than 3% mutation rate change), because the mutation rate was calculated based on a single reference.
Assess whether the mutations would cause amino acid changes. This task requires reading the genome sequence and find its corresponding amino acid changes from literature and data sources. a. For teams, describe what each member worked on.
No team members were involved in this project. - What is new or novel about your project?
The novelty of this project is that I first proved that the virus mutation is predictable. Still, the mutation trends are different for different genome sites and different geographical locations.
Secondly, most studies focused on the prediction of COVID-19 cases, and very few studies focus on single-site mutation prediction. I used a relatively simple model to predict the trends for each site which could be a useful innovation.
Additionally, I used public data to proceed with this project. It can be called data reuse or data mining. In my project, a website is under construction to collect this public data, visualize it and make predictions in real-time to better popularize this important genetic information. a. Is there some aspect of your project’s objective, or how you achieved it that you haven’t done before?
Yes, there are plenty of aspects that I haven’t done before. For example, although I used the model (ARIMA) before, applying the model on genome sequence mutation rate is something I haven’t done before. For past projects, I could apply modeling directly on the raw data; but in this project, I had to understand and calculated time series out of the raw data before modeling could be applied. Besides, the bioinformatics aspect of the project’s objective is another new challenge for me. I tried to combine knowledge of biology and mathematical modeling to solve prediction problems. The transformation and interpretation of knowledge brought about by inter-disciplinary have not been encountered in my previous studies. b. Is your project’s objective or the way you implemented it, different from anything you have seen?
Yes, most of the website database which we have seen before is only showing the raw data or some processed data, such as GeneBank from NCBI (The National Center for Biotechnology Information), GISAID (a global science initiative and primary source) and CNCB-2019nCoVR (China National Center for Bioinformation 2019 Novel Coronavirus Resource) database. Most of them are focusing on showing the data in many statistical ways, however, they didn’t do the prediction on the mutation yet. c. If you believe your work to be unique in some way, what research have you done to confirm that it is?
For start, I had done a literature review on COVID-19 predictions, and I find that most of them which may be related to my project are focusing on the statistic on SARS-COV-2, such as comparing the mutation of virus in a different region to trace to the source, or prediction on the cases number, or predictions on the effect of amino acids and proteins. Diverse mutation of virus in different regions is consistent with other reports which confirm the reliability of my results. - What was the most challenging part of completing your project?
In my project, the most difficult thing is to understand the expertise from vastly different research areas and to combine the knowledge.
My project is a product entirely of my own design, and it is not aligned with any of the main research topics of my previous experience and all the researchers we were able to ask for help from. It is totally exciting to do it independently, but it is challenging for me to understand all the math, computer science, and biology knowledge from experts’ inputs and proceed with the project on my own with a few experts supervise and suggestions.
Besides consulting to obtain suggestions and validate them by trial-and-error, I often needed to translate the computational based work into a different, biological language, describing the modeling reasoning in a way that can be understood by a bioinformatics researcher, or put the genome sequence data into something meaningful for a pure mathematician.
Working on a new interdisciplinary project, without any professional forerunners, sometimes get me into communication issues (such as the terminology across different research areas that can cause misconception). For example, during the data collection, the data suggested by the biology experts did not meet the requirements suggested by my computer science advisor. I had to work carefully to validate all the data, suggestions, and requirements to make sure I did not train the model with some wrong data.
a. What problems did you encounter, and how did you overcome them?
Learning specialized research articles from different research areas was a big challenge. My solution was to put more effort and more time into the project. I checked new concepts on the web and read research articles over and over again. I also kept close contact with some experts and ask them for directions on how to learn that new knowledge.
Combining knowledge from different research areas requires a lot of back-and-forth communications and validations. For example, for the biology questions – which important site may affect the structure of a virus, I would learn from a biology expert and used the biological criteria to select an important genome site. With that knowledge, I turned to an expert in math modeling and asked him for the suggestion on how to build models for quickly changing time series. The results of the modeling must be explained and validated in biology backgrounds, and I had to figure out the biological meaning of the parameters and predictions and explained to my biology advisor so we can validate the model and change the parameters and do another round of model fitting.
During the programming, because the size of data was very large, I needed to build codes for the “batch” operation of a group of files, even for very simple tasks. I had to carefully debug the code and used unit-testing very frequently.
b. What did you learn from overcoming these problems?
I learned how to explain things in different ways to experts in different areas. Such as when I’m trying to explain the meaning of data to a modeling expert, I have to use the mathematical way to explain it. So, he can give me a more specific suggestion on how to design the model based on the mutation rate data. And after I built the model, I have to explain the predictions to biology experts using a biology tone.
- If you were going to do this project again, are there any things you would do differently the next time?
I could choose to use and compare more professional models for prediction. Some other Machine learning models are reported to be very powerful in doing predictions for time series too, and if I have more time, I would add AI models into the predictions.
With more knowledge on the biology data and database, I could more easily design a better data collection process so I will not waste time and effort on wrong data or wrong formats.
Time management throughout the year. I would start the project earlier, to make time for other important school and science events during the project year.
a. Did working on this project give you any ideas for other projects?
Working on this project gave me quite a lot of ideas in using mathematics and computer science in the biology area like using simple modeling for protein prediction and in the computer science area like using machine learning and AI for modeling and prediction on virus mutation or medical diagnosis.