Fall 2023: Classifying Transposons using DeepTE. A multi-CNN model. My team of four including myself enjoyed analyzing the paper results, we utilized publicly available transposons from the Zenodo library and its metadata to extract the TEs of C-Elegans and O-Sativa. We then exported the data to multiple CSV files and fasta files for preprocessing and selection for partial training and testing DeepTE. My main contribution was through writing many scripts, python and SBatch to run DeepTE classification on the O-Sativa transposons as well as on the data file provided by the author. We had regular meetings throughout the semester and put together dynamic plans that we often revisited to compare classification results on O-Sativa versus the author-provided data. We created a presentation to demonstrate our findings.
During the past year, I presented and created six different presentations both individually and collaboratively with my colleagues. Three of my presentations were in-person and two were video recordings. The topics of my presentations varied but all used references that were listed on one slide.
let me tell you about my presentaions here.
Genomics
My Genomics video presentation topic was “Covid Origins,” in which I reviewed the peer-reviewed publication noted below and presented some of the main analyses and scientific methods used by the researchers.
Refrence
Pekar, J. E., Magee, A., Parker, E., Moshiri, N., Izhikevich, K., Havens, J. L., Gangavarapu, K., Malpica Serrano, L. M., Crits-Christoph, A., Matteson, N. L., Zeller, M., Levy, J. I., Wang, J. C., Hughes, S., Lee, J., Park, H., Park, S., Zi Yan, K. C., Pin Lin, R. T., . . . Wertheim, J. O. (2022). The molecular epidemiology of multiple zoonotic origins of SARS-CoV-2. Science. https://doi.org/abp8337
DeepTE
The first semester was full of excitement, and by its end, I had completed multiple presentations, including one that utilized Convolutional Neural Networks (CNN) to classify transposons. The final presentation at the end of the semester was a collaborative effort between my colleagues and me. Together, we worked on creating a PowerPoint to showcase our findings and address any errors.
Refrences
Yan, H., Bombarely, A., & Li, S. (2020). DeepTE: A computational method for de novo classification of transposons with convolutional neural network. Bioinformatics, 36(15), 4269-4275. https://doi.org/10.1093/bioinformatics/btaa519
Ethics
Another presentation as part of my ethics in biomedical research class, which involved an analysis promoting academic and research integrity with adherence to R3 principles.
Refrence
Yu, H., Wang, X., Bai, L., Tang, G., Carter, K. T., Cui, J., Huang, P., Liang, L., Ding, Y., Cai, M., Huang, M., Liu, H., Cao, G., Gallinger, S., Pai, R. K., Buchanan, D. D., Win, A. K., Newcomb, P. A., Wang, J., Grady, W. M., … Luo, Y. (2023). DNA methylation profile in CpG-depleted regions uncovers a high-risk subtype of early-stage colorectal cancer. Journal of the National Cancer Institute, 115(1), 52–61. https://doi.org/10.1093/jnci/djac183
Plant Pathogen Gene Silencing
This presentation was a collaborative effort between two individuals. Delivering this presentation not only enhanced my understanding of scientific innovations in the field of biological methods for plant disease but also helped me develop my collaborative and leadership skills.
Refrence
Qiao, L., Lan, C., Capriotti, L., Ah-Fong, A., Nino Sanchez, J., Hamby, R., Heller, J., Zhao, H., Glass, N. L., Judelson, H. S., Mezzetti, B., Niu, D., & Jin, H. (2021). Spray-induced gene silencing for disease control is dependent on the efficiency of pathogen RNA uptake. Plant biotechnology journal, 19(9), 1756–1768. https://doi.org/10.1111/pbi.13589
Cellular Engineering and Base Editing
The first presentation was a component of my cellular engineering coursework, where I discussed base editing using a selected peer-reviewed paper authored by Komor et al, published in 2017. My presentation covered the historical background of base editing, the materials and methods, the experiments conducted, the conclusions drawn, and the results obtained.
Refrences
Komor, A. C., Zhao, K. T., Packer, M. S., Gaudelli, N. M., Waterbury, A. L., Koblan, L. W., Kim, Y. B., Badran, A. H., & Liu, D. R. (2017). Improved base excision repair inhibition and bacteriophage Mu Gam protein yields C:G-to-T:A base editors with higher efficiency and product purity. Science advances, 3(8), eaao4774. https://doi.org/10.1126/sciadv.aao4774
Working with Illumina reads requires assessing the quality of raw reads as a first step. Then through a series of bioinformatic tools of multiple processing steps, we enhance the read quality. I used Trimmomatic to trim adapters and fastqc to visualize the results. unlike Ecoli reads the Rat reads were larger and required processing time on the assigned GPU that exceeded the allocated time budget, this made it harder to create a single slurm-batch and a pipeline to perform all steps. I’m sharing the results of trimmomatic for pair-end reads with the 1P (shown in lower row) and 2P as well as 1U (shown in upper row) and 2U, from which we can see how the selected paired result shows consistently higher quality of read in the lower right corner, while the unpaired read on the top left corner shows varying read quality.
Use each of these sections to highlight on focused points of your portfolio projects. This could be in-depth details on what it means for the audience or what you want them to know.
Use each of these sections to highlight on focused points of your portfolio projects. This could be in-depth details on what it means for the audience or what you want them to know.
Use each of these sections to highlight on focused points of your portfolio projects. This could be in-depth details on what it means for the audience or what you want them to know.
Use each of these sections to highlight on focused points of your portfolio projects. This could be in-depth details on what it means for the audience or what you want them to know.
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