Huma Shehwana

Info

Huma Shehwana
Postdoctoral fellow (Johan Westerhuis group)

Work address

Biosystems Data Analysis, University of Amsterdam 
Room C2.204, Science Park 904, 1098 XH, Amsterdam 
Email: h.shehwana@uva.nl 

Professional Career

I earned my Bachelor’s degree in Bioinformatics from the International Islamic University in Pakistan. Following that, I moved to Turkey, where I completed my Ph.D. in the Department of Molecular Biology and Genetics at Bilkent University in September 2017. My doctoral research focused on identifying prognostic and diagnostic biomarkers for estrogen receptor-negative breast cancer subtypes using bioinformatics approaches. This involved analyzing transcriptomic datasets (both microarray and RNA-seq) and developing automated data analysis tools using Shiny web applications. 

After completing my Ph.D., I served as an Assistant Professor at the National University of Medical Sciences in Pakistan from April 2018 to August 2021. During this period, I also worked as a postdoctoral fellow at the MD Anderson Cancer Center, University of Texas, USA (November 2019 – October 2020). There, my research focused on developing tools for metabolomics and proteomics data analysis using mass spectrometry and reverse phase protein array (RPPA) technology. 

In September 2021, I relocated to the Netherlands and joined the Netherlands Cancer Institute (NKI) as a postdoctoral fellow (October 2021 – May 2023). At NKI, my work centered on DNA sequencing data analysis and the development of automated pipelines for processing various genomics datasets. Driven by a growing interest in machine learning, I accepted a temporary postdoctoral position at Utrecht University’s Department of Social Sciences in August 2023, where I worked for 10 months. My role involved developing a method to impute missing data using the XGBoost machine learning algorithm. 

Most recently, in February 2025, I began a new postdoctoral position at the University of Amsterdam (UvA), where I am currently continuing my research. 

Research

At the University of Amsterdam, I am involved in the Next Generation Immuno-Dermatology (NGID) project—an initiative aimed at transforming the treatment and long-term care of patients with chronic inflammatory skin diseases. The main goal of NGID is to develop personalized and rational treatment strategies that can ensure disease control, prevent progression, and reduce the risk of later-in-life comorbidities. As part of this effort, the project involves collecting and analyzing multi-omics datasets—including RNA sequencing, metabolomics, and proteomics—from patients enrolled in various clinical trials. 

My specific role in the project focuses on the integration of multi-omics data, particularly from advanced single-cell imaging technologies such as mass cytometry and MALDI mass spectrometry imaging, in combination with LC-MS and RNA-seq data. The aim is to uncover shared biological signatures across omics layers and to identify layer-specific biomarkers. Additionally, I will contribute to the development of novel computational methods to enhance the integration and interpretation of these complex, high-dimensional datasets. Ultimately, I hope this work will advance precision medicine approaches in the field of immuno dermatology.