Eran Elhaik

Eran Elhaik

Senior lecturer

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Personal profile


My research in population, medical, and evolutionary genomics spans several different subfields, including Computational Biology or Bioinformatics, Epigenetics, Microbiome, Molecular evolution, Epidemiology, and Forensics. More recently I began using machine learning to answer some of these questions. In my research, I am trying to identify interesting and open questions concerning evolutionary, molecular, or epidemiological processes with respect to various organisms and address them using existing or novel tools.

In my population genetic research, I study the origin of populations and what can that teach us about their history, diseases susceptibility, and more using modern and ancient data. I am developing computational tools to trace and date ancient genomes. Metagenomes are powerful tools to answer such questions, which I explore as part of the MetaSUB Consortium. Because questions of origins are invariably linked with ancestry and identity, my work has immediate applications for medical and genetic research where the homogeneity of cohorts is of importance, as well as to social studies which ask similar questions from different angles. I thereby collaborate with social, life, and biomedical scientists.

In my medical genetic research, I study complex disorders, like sudden infant death syndrome (SIDS or cot death) and mental disorders. I also collaborate with groups that study multiple myeloma, amyotrophic lateral sclerosis (ALS), and spina bifida. Our goal is to decipher the etiology of these disorders by identifying environmental risk factors and genomic loci associated with the conditions.

In my evolutionary work, I strive to understand how genomic material is organized in genomes. What evolutionary processes govern and maintain the organization and content of junk DNA and to what purpose.

I also design and develop various platforms (e.g., the GenoChip and DREAM microarrays) and genetic solutions (e.g., GPS Origins, Ancient DNA Origins) for industry and government. The Ancient DNA Origins test represents the latest achievement in ancestry test that allows evaluating the user's DNA against the ancient DNA of ancient people from various cultures.

In the past decade years, I collaborated with researchers from over 100 countries. My past funders include National Geographic, National Science Foundation (NSF), The Royal Society, UK Medical Research Council (MRC), UK Engineering and Physical Sciences Research Council (EPSRC), The Grantham Foundation, The University of Sheffield, and the DNA Diagnostics Centre.

My research is currently supported by the VR (The Swedish Research Council), Erik Philip-Sörensen Foundation, Crafoord Foundation, and SLU GroGrund.

My lab is strictly computational, and I am always looking for students with strong computational skills interested in studying truly interesting questions. 

  • 2021-: Docent in Genetics, Department of Biology, Lund University.
  • 2019-2021: Associate Professor in the Department of Biology, Lund University, Sweden.
  • 2014-2019: Lecturer in Animal and Plant Sciences. University of Sheffield, UK.
  • 2013 (6 mo): Research Associate in Mental Health. Johns Hopkins University, School of Public Health, Maryland.
  • 2011-2013: Postdoctoral Fellow in Mental Health. Johns Hopkins University, School of Public Health, Maryland. Advisor: Prof. Peter Zandi.
  • 2009-2011: Postdoctoral Fellow in Population Genetics. Johns Hopkins University, School of Medicine, Maryland. Advisor: Prof. Aravinda Chakravarti.
  • 2004-2009: Ph.D. in Molecular Evolution. University of Houston, Texas. Title of Doctorate: The Compositional Organization of Mammalian Genomes: Characteristics and Evolution. Dissertation Supervisor: Prof. Dan Graur.


I teach courses that are part of Lund University Master's program in Bioinformatics, including Bioinformatics and Sequence Analysis (BINP11), Programming in Python (BINP16), DNA Sequencing Informatics I (BINP28), DNA Sequencing Informatics II (BINP29), and Research Project (BINP37-39 and BINP50-51). 


Societal impact

Selected news coverage (past 10 years): 

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being
  • SDG 11 - Sustainable Cities and Communities
  • SDG 15 - Life on Land

UKÄ subject classification

  • Forensic Science
  • Genetics
  • Evolutionary Biology

Free keywords

  • Computational biology
  • Bioinformatics
  • Population genetics
  • Genetics
  • Epigenetics
  • Microbiome
  • Big Data
  • Machine learning
  • Molecular evolution
  • Epidemiology
  • Forensics
  • Sudden Infant Death Syndrome
  • Artificial Intelligence (AI)


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Collaborations and top research areas from the last five years

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