Hussein Mohsen

Postdoctoral Fellow · Memorial Sloan Kettering Cancer Center · He/him

I am a Postdoctoral Research Fellow at the Morris and Carrot-Zhang Labs, Memorial Sloan Kettering Cancer Center. My research interests are centered on interpretable machine learning and somatic-germline interactions in cancer. I received my PhD in Computational Biology and Bioinformatics and MA in History of Science and Medicine from Yale University, MS in Bioinformatics from IU, and BS in Computer Science from LAU.

I am an avid urbanite, have been to 64 cities, lived in 6, and have 31415926535 on the list. More on why here. This filmmaker is phenomenal. This paper affected the way I do science (and to an extent everyday life). The idea of having short sentences is from here.

Sporadically, I host episodes on NBN's History of Science podcast.


Research Papers

T. Qing*, H. Mohsen*, V. Cannataro, M. Marczyk, M. Rozenblit, J. Foldi, M. Murray, J. Townsend, Y. Kluger, M. Gerstein, and L. Pusztai (2022). Cancer Relevance of Human Genes, Journal of the National Cancer Institute, djac068.  

H. Mohsen, V. Gunasekharan, T. Qing, M. Seay, Y. Surovtseva, S. Negahban, Z. Szallasi, L. Pusztai, and M. Gerstein (2021). Network propagation-based prioritization of long tail genes in 17 cancer types, Genome Biology, 22, 287.  

T. Qing, H. Mohsen, M. Marczyk, Y. Ye, T. O’Meara, H. Zhao, J.P. Townsend, M. Gerstein, C. Hatzis, Y. Kluger and L. Pusztai (2020). Germline variant burden in cancer genes correlates with age at diagnosis and somatic mutation burden, Nature Communications, 11, 2438.  

H. Mohsen, J. Warrell, M.R. Min, S. Negahban, and M. Gerstein (2020). Weight-based Neural Network Interpretability using Activation Tuning and Personalized Products, Machine Learning in Computational Biology Workshop 2020 (MLCB'20).  

M. Amodio, D. van Dijk, K. Srinivasan, W.S. Chen, H. Mohsen, K.R. Moon, A. Campbell, Y. Zhao, X. Wang, M. Venkataswamy, A. Desai, V. Ravi, P. Kumar, R. Montgomery, G. Wolf, and S. Krishnaswamy (2019). Exploring Single-Cell Data with Deep Multitasking Neural Networks, Nature Methods, 16, pp. 1139–1145.  

S. Lou, K.A. Cotter, T. Li, J. Liang, H. Mohsen, J. Liu, J. Zhang, S. Cohen, J. Xu, H. Yu, M. Rubin, and M. Gerstein (2019). GRAM: A generalized model to predict the molecular effect of a non-coding variant in a cell-type specific manner, PLoS Genetics, 15 (8): e1007860.  

J. Warrell, H. Mohsen, and M. Gerstein (2018). Rank Projection Trees for Multilevel Neural Network Interpretation, NeurIPS Machine Learning for Health Workshop (NeurIPS'18 ML4H).  

H. Mohsen, H. Tang, and Y. Ye (2017). DNPipe: Improving De Novo Metatranscriptome Assembly via Machine Learning Algorithms, International Journal of Computational Biology and Drug Design (IJCBDD), 2 (10), pp. 91-107.  

H. Mohsen, H. Kurban, K. Zimmer, M. Jenne, and M. Dalkilic (2015). Red-RF: Reduced Random Forests using priority voting dynamic data reduction, IEEE International Congress on Big Data (IEEE BigData Congress'15), pp. 118-125.  

H. Mohsen, H. Kurban, M. Jenne, and M. Dalkilic (2014). A New Set of Random Forests with Varying Dynamic Data Reduction and Voting Techniques, IEEE International Conference on Data Science and Advanced Analytics (IEEE DSAA’14), pp. 309-405.  

N. Mansour and H. Mohsen (2014). Computational Evaluation of Protein Energy Functions, International Conference on Intelligent Computing (ICIC’14), Lecture Notes in Computer Science (LNCS): Intelligent Computing in Bioinformatics, 8590, pp. 288-299.  

H. Mohsen (2014). A Model to Measure Inter-communication between Segregated Communities, IEEE International Conference on Behavioral, Economic and Social Computing (IEEE BESC'14), pp. 1-6.  

H. Mohsen, M. Fawaz, and K. Jahed (2011). Multi-Purpose Speech Recognition and Speech Synthesis System, IEEE Multidisciplinary Engineering Education Magazine (IEEE MEEM), 6 (4), pp. 22-27.

Reviews & Commentary

H. Mohsen (2020). Race and Genetics: Somber History, Troubled Present, Yale Journal of Biology and Medicine, 93 (1), pp. 215-219.  

F.C.P. Navarro, H. Mohsen, C. Yan, S. Li, M. Gu, W. Meyerson, and M. Gerstein (2019). Genomics and data science: an application within an umbrella, Genome Biology, 20 (109).  


SEP 2020 | American Association for Cancer Research (AACR) Scholar-In-Training Award

SEP 2019 | Franke Fellowship in Science and the Humanities (2019-2020)

AUG 2016 | Gruber Science Doctoral Fellowship (2016-2019)

AUG 2013 | Fulbright Graduate Scholarship (2013-2015)

SEP 2012 | Erasmus Mundus Postgraduate Exchange Scholarship (2012-2013)

JUN 2011 | Best Computer Science Capstone Project Award - LAU Class of 2011

JUL 2010 | 2nd Place - Nokia-NNA contest for mobile application development in Lebanon

JUL 2010 | Extreme Programmer Award - ACM Lebanese Collegiate Programming Contest 2010, Beirut, Lebanon

2009-2011 | Lebanese American University (LAU) Honor List

SEP 2008 | LAU Undergraduate Merit Scholarship (2008-2011)


APR 2022 | New paper on the spectrum of human gene cancer relevance is out in the Journal of the National Cancer Institute

OCT 2021 | New paper on prioritizing long tail genes in cancer using network propagation is out in Genome Biology

AUG 2021 | Happy to have joined NBN History of Science as a Host

NOV 2020 | Our submission on weight-based neural network interpretability is accepted at MLCB'20

OCT 2020 | My interview with the Mellon Sawyer Seminar at Yale, The Order of Multitudes, is out

SEP 2020 | Happy to have received an AACR Scholar-In-Training Award

MAY 2020 | New paper on germline and somatic variation burden in cancer is out in Nature Communications

MAR 2020 | My Perspectives piece on the history of race and genetics is out in YJBM

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