2024 recipients of the MSF Computational Biology Fellowship Program in MM.

Minghao Dang

Minghao earned his Ph.D. in 2017 from the Institute of Biophysics, Chinese Academy of Sciences. Following his initial postdoctoral training, Minghao joined Dr. Linghua Wang’s lab at MDACC in 2019 where he received comprehensive training in applying innovative bioinformatics approaches to dissect the tumor ‘ecosystem,’ deeply profiling tumor cells, cells of the tumor microenvironment (TME), and exploring tumor-immune-stroma crosstalk at single-cell resolution across many cancer types.  Since 2020, Minghao has focused his research in multiple myeloma (MM), contributing to several projects such as the single-cell profiling of BCMA naïve vs. refractory relapsed MM patients (ASH 2022), integrative genomic and transcriptomic profiling of MM precursors in a prospective longitudinal observational study (AACR 2023), single-cell multi-omic data analysis of TME evolution across the disease spectrum of MM (ASH 2023), and single-cell multi-omic data analysis of clonotypic and transcriptional evolution of MM precursor disease (Cancer Cell 2023).

Minghao Dang headshot
Minghao Dang, PhD
The University of Texas MD Anderson Cancer Center logo

As a recipient of the MSF Fellowship in 2024, Minghao is now an Associate Data Scientist under the mentorship of Dr. Linghua Wang and Dr. Robert Orlowski.  Minghao’s research as an MSF Fellow will focus the use of  single cell multi-omics data analysis to dissect tumor heterogeneity, tumor evolution and dynamics of TME remodeling during the progression of multiple, with special attention to the t(4;14) subtype.

Nina Murrell

Nina is a Bioinformatics Programmer in Applied Bioinformatics Labs and Precision Medicine at NYU Langone. She holds a MSc in Bioinformatics and Systems Biology from the Technical University of Denmark and a BS degree in Chemistry from UNC Chapel Hill. Under the mentorship of Dr. Gareth Morgan and Dr. Aristotelis Tsirigos, Nina’s research will investigate the role of chromatin organization in cancer and how we can utilize machine learning to revolutionize the understanding, diagnosis, and treatment of cancer.

Nina Murrell headshot
Nina Murrell, MSc
NYU Langone Health logo

Michael Durante

Michael is a Hematology/Oncology Fellow at Sylvester Comprehensive Cancer Center, part of UHealth – the University of Miami Health System, and Jackson Memorial Hospital as part of the Physician Scientist Training Program. He completed his MD/PhD training at the University of Miami’s Medical Scientist Training Program in cancer biology with over 20 peer-reviewed publications. He has been a part of Drs. Landgren and Maura’s computational myeloma laboratory since 2022 and is a co-author in numerous publications including journals such as Nature Medicine and Journal of Clinical Oncology. Michael seeks to apply his extensive computational expertise to develop and utilize cutting-edge computational models to predict disease progression, treatment responses, and outcomes for individuals with high-risk multiple myeloma. Michael has a special interest identifying mechanisms of resistance in multiple myeloma patients undergoing modern targeted and cellular immunotherapies. Michael’s fellowship mentors are C. Ola Landgren, MD, PhD and Francesco Maura, MD.

Michael Durante headshot
Michael Durante, MD, PhD
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