Ph.D. candiate, David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada.
Thesis: "Application of Deep Learning in Quantitative Proteomics", supervised by Dr. Ming Li
We are the first to propose a deep learning based model, DeepIso, that combines recent advances in Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) to detect peptide features from Liquid Chromatography Mass Spectrometry (LC-MS) data, a key step in quantitative proteomics that holds considerable promise for disease biomarker detection. Next, we develop PointIso, through point cloud based models and attention based segmentation. It allows arbitrary precision and high dimensional data processing to obtain more desirable properties for the analysis of complex peptide mixtures. Our models are already showing better accuracy than the other existing algorithms based on the benchmark dataset obtained by widely used Orbitrap instrument. We are extending this model to support 4D LC-MS data obtained from more advanced mass spectrometer, namely, TimsTOF instrument. Besides that, we are working to incorporate our model in the pipeline of Label Free Quantification (LFQ) to make it more appealing in the proteomics society.
Publications:
Zohora, F.T., Rahman, M.Z., Tran, N.H., Xin, L., Shan, B. and Li, M., 2021. Deep neural network for detecting arbitrary precision peptide features through attention based segmentation. Scientific reports, 11(1), pp.1-16.
Zohora, F.T., Rahman, M.Z., Tran, N.H., Xin, L., Shan, B. and Li, M., 2019. Deepiso: A deep learning model for peptide feature detection from lc-ms map. Scientific reports,9(1), pp.1-13.
Zohora, F.T., Tran, N.H., Zhang, X., Xin, L., Shan, B. and Li, M., 2017. Deepiso: a deep learning model for peptide feature detection. arXiv preprint arXiv:1801.01539
M.Sc.Engg.(CSE), Department of Computer Science & Engineering (CSE), Bangladesh University of Engineering and Technology (BUET).
Year of passing: 2014
Thesis: "The Consensus String Matching Problem and The Diagnosis of Allelic Heterogeneity", supervised by Dr. M. Sohel Rahman
In this thesis, we first show the NP-hardness of the consensus string problem under two well known mutation types, namely inversion and transposition as the distance metric. Then we propose a polynomial time algorithm for the relaxed version of the problem which determines the existence of a consensus sequence given two input sequences under the inversion and transposition metric. Finally, we present a pathway of detecting Allelic Heterogeneity, a challenging genetic disease, using our algorithm.
Conference Publication: Fatema Tuz Zohora, M. Sohel Rahman, "Application of Consensus String Matching in the Diagnosis of Allelic Heterogeneity - (Extended Abstract)", Bioinformatics Research and Applications, Lecture Notes in Computer Science Volume 8492, 2014, pp 163-175 (in the Proceedings of International Symposium on Bioinformatics Research and Applications (ISBRA 2014), Zhangjiajie, China, 2014)
Journal Publication:
Zohora, Fatema Tuz, and M. Sohel Rahman. "An efficient algorithm to detect common ancestor genes for non-overlapping inversion and applications." Theoretical Computer Science (2016).
Zohora, Fatema Tuz, and M. Sohel Rahman. "Application of consensus string matching in the diagnosis of allelic heterogeneity involving transposition mutation." International journal of data mining and bioinformatics 13.4 (2015): 360-377.
B.Sc.Engg.(CSE), Department of Computer Science & Engineering (CSE), Bangladesh University of Engineering and Technology (BUET).
Year of passing: 2012
Thesis: "Longest Common Almost Increasing Subsequence", supervised by Dr. M. Sohel Rahman
In this thesis, I researched on variations of well-known LCS problem in the field of theoretical computer science and implemented an algorithm to find out Longest Common Almost Increasing Subsequence.
Journal Publication: (in order of author's last name) Johra Muhammad Moosa, M. Sohel Rahman, and Fatema Tuz Zohora, "Computing a Longest Common Subsequence that is Almost Increasing on Sequences Having No Repeated Elements", Journal of Discrete Algorithms, Elsevier, Volume 20:12–20, 2013
Higher Secondary Certificate (HSC), board of Dhaka, Bangladesh
Year of passing: 2006
CGPA: 5.00 (out of 5.00)
Secondary School Certificate (SSC), board of Dhaka, Bangladesh
Year of passing: 2004
CGPA 5.00 (out of 5.00)
Awards:
University of Waterloo offered International Doctoral Student Award, Graduate Research Studentship, and Doctoral Entrance Award-Women
Awarded Dean's list for three consecutive academic years (second year, third year and fourth year) in B.Sc.Engg.(CSE)
General grade scholarship of Dhaka Division for Higher Secondary Certificate (high school) result
General grade scholarship of Dhaka Division for Secondary School Certificate (junior high school) result
CV: