Dr. Amit Singh

Dr. Amit Singh

Staff of Professorship for Biomechanics

ETH Zürich

Institut für Biomechanik

GLC H 20.1

Gloriastrasse 37/ 39

8092 Zürich

Switzerland

Additional information

Research area

My research focuses on the intersection of bioinformatics and systems biology, primarily focusing on genomics and transcriptomics analysis using bioinformatics software tools. Additionally, I specialize in developing ETL data pipelines for efficiently processing large datasets and performing downstream analysis using machine learning techniques. I am particularly interested in taking systems biology approaches such as modelling large-scale networks and signalling pathways to understand biological processes  better. To achieve this, I use various methods  for example, Boolean modelling, agent-based modelling, network optimization, Ordinary Differential Equations (ODEs), parameter estimation from experimental data, identifiability analysis, bifurcation analysis, and sensitivity analysis. My ultimate goal is to deepen our understanding of the complex molecular mechanisms underlying biological systems and to identify new therapeutic targets for diseases.

 

Dr. Amit Singh is a bioinformatic data scientist. He holds a bachelor's degree in Physics and a master's degree in Biochemistry. After completing his master's, he worked as a project associate at the Department of Biotechnology at the Indian Institute of Technology (IITcall_made) in Madaras. Dr. Singh later moved to the University of Rostock at the faculty of computer science and electrical engineering in the Department of Systems Biology and Bioinformatics (SBIcall_made), where he worked as a research assistant on the Cancer and Aging Link through Systems Biology (CALSYS) project. He then completed a PhD project on the Systems Biology of Wound Healing in the MedSys-Chronic Wounds project at Heidelberg University (BioQuantcall_made). He also conducted research on PC12 cell differentiation at the University of Freiburg (FRIAScall_made) where he obtained his PhD in 2015. After completing his PhD, Dr. Singh worked as a postdoctoral researcher at the Max Planck Institute for Molecular Biomedicine (MPIcall_made) in Münster, Germany, in 2016. He then moved to Heidelberg University's Biochemistry Department as a bioinformatic data scientist. Additionally, he holds an honorary position at Oxford University, UK. Dr. Singh has been a scientific collaborator at ETH Zurich's Institute for Biomechanics (LBB) since 2022.

Membership

Since Membership
2022 LS2 Life Sciences Switzerland

Additional information

  I have a deep passion for systems biology and interdisciplinary research. My educational journey has spanned across various fields, including physics and mathematics at the undergraduate level, experimental biochemistry at the master's level, and bioinformatic and systems biology at the doctoral level. This diverse educational background allows me to seamlessly bridge the gap between experimental and computational biologists, facilitating productive collaboration in interdisciplinary research. Over a decade ago, I started my career as a computational biologist, primarily focusing on bioinformatics and systems biology. Since then, I have actively participated in numerous interdisciplinary projects, leveraging my skills to contribute significantly to the research outcomes. I've developed mathematical models to explore dynamic behaviour in various biological processes, such as G2-M cell cycle progression, keratinocyte cell migration in wound healing, PC12 cell differentiation, and the light-dark entrained circadian clock of Neurospora crassa. My contributions to these projects include Boolean modelling, network optimization, Ordinary Differential Equations (ODEs), parameter estimation, identifiability analysis, bifurcation analysis, and sensitivity analysis. I took up a postdoctoral fellowship at the Max Planck Institute of Biomedicine in Munster, where I led the implementation of an RNA sequencing and chip sequencing analysis pipeline to gain insights into the formation of long bones during the embryonic and early postnatal stages of mice. Since then, I have been intensively involved in various bioinformatic projects related to mouse bone and ageing research. My contributions have primarily focused on implementing diverse next-generation sequencing (NGS) analysis pipelines, including but not limited to spatial transcriptomics, single-cell sequencing, bulk RNA sequencing, ATAC sequencing, and proteomic data analysis.

 

Apply for student project

 

 If you are looking for Bachelor's and Master's thesis projects, please contact me "amit.singh@hest.ethz.ch"  The following task is available.

1. Unravelling the spatial and biomechanical dynamic of fracture healing in mice

2. Exploring the Impact of Sclerostin Antibody Treatment on Bone Remodeling through Single-Cell Mechanomics Cluster Analysis

3. Advancements in Micro-CT Image Analysis Framework for the MI-CT Repository

4. Mathematical models for optimizing experimental design and scale up of bone organoids 

 

 

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