Ayesha Kawser

Looking for research assistant position in bioinformatics

Research Student

University of Manchester, UK

• Currently utilizing fixed module repertoire with 56,000 blood transcriptomics data using R (NHS collaboration) to identify biomarkers for type 1 interferenopathies
• Built a new prediction tool based on deep learning techniques to predict S palmitoylation sites in Arabidopsis Thaliana using Python and 18930 peptides which achieved an AUC score near 1. Used Jupyter Notebook as the computing platform.
• Weekly meeting with team members in the lab to discuss progress

GenomicHub, Virtual

• Utilizing Unicyler and Pilon in BV-BRC for quality check, control, and filling gaps and PATRIC and RAST for annotation in metagenomic samples
• Employed PlastFlow in Galaxy for prediction of plasmid sequence and assembling in Galaxy
• Utilizing BV-BRC for taxonomic classification, functional and diversity analysis

• Built a database for miRNA diseases where the user can search for specific miRNA, diseases, and genes based on confidence scores.
• Built ion statistics calculator using function and argparse which can count the number of peptides depending on range size and specific window size.
• Conducted RNA-seq analysis and sequence analysis and visualization through IGV.
• Learned different computational biology techniques such as the PCA, hierarchical and k-means clustering, and network analysis
• Learned about different kinds of hypothesis tests such as the Fisher’s F test, paired and unpaired t-test and Pearson chi-squared test, regression analysis, and ANOVA.

MSc in Bioinformatics at the University of Manchester

BSc in Biological science at the University of Toronto