Debora Marks

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Debora Marks
Structural Biology, Bioinformatics
InstitutionsHarvard Medical School
Thesis (2010)
Doctoral advisorReinhard Heinrich, Hanspeter Herzl
Websitehttps://marks.hms.harvard.edu/

Debora S. Marks is a researcher in

Systems Biology at Harvard Medical School.[1]
Her research uses computational approaches to address a variety of biological problems.

Career and research

After an undergraduate degree in medicine she worked in the pharmaceutical industry, coming back to research late in life through a mathematics degree from the

microRNAs in the early 2000s[2][3][4] and her work on the biology of microRNAs eventually became a PhD thesis, which she submitted under the guidance of Reinhart Heinrich to Humboldt University of Berlin in 2010.[5] One key contribution was her discovery that transfection of microRNAs into cells counter-intuitively increases the expression of some genes, due to competition for the cellular machinery that processes small RNAs.[6] In collaboration with Alexander van Oudenaarden and Nils Bluthgen, she showed that microRNAs reduce the noise in protein expression when mRNA levels are low, reducing the likelihood of unwanted protein expression as a result of leakage at a gene's promoter.[7]

She is best known for her work on protein structure prediction: her method, which draws on an approach from statistical physics, maximum entropy under constraint, uses correlations between the sequences of protein family members from multiple species to build models of protein structure from sequence alone.[8] In some cases the predicted models are sufficiently accurate to permit molecular replacement of the model into X-ray crystallography data, facilitating phase replacement.[9] The algorithm[10] has been extensively used by other researchers to predict and gain insights into protein structures, for example the structures of the σ2 receptor[11] and the tetraspanin CD81.[12] Marks and her close collaborator Chris Sander have shown that this approach can also be used to predict the structures of non-coding RNAs and RNA-protein complexes,[13] to identify otherwise undetectable structured states in disordered proteins[14] and to predict the functional effects of sequence mutations.[15]

Awards

In 2016, Marks was awarded the Overton Prize by the International Society for Computational Biology.[16]

In 2018, Marks was awarded the Ben Barres Early Career Award by the Chan Zuckerberg Initiative as part of the Neurodegeneration Challenge Network.[17]

In 2022, Marks was elected as a Fellow of the International Society for Computational Biology.[18]

References

  1. ^ "Debora S. Marks Lab". Retrieved July 11, 2016.
  2. ^ a b "2016 Overton Prize: Debora Marks". www.iscb.org. Retrieved January 1, 2019.
  3. PMID 14709173
    .
  4. PMID 15502875
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  5. PMID 27429747
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  6. PMID 19465925
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  7. S2CID 206633133
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  8. PMID 22579045
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  9. PMID 29590088
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  10. ^ "EVcouplings". evfold.org. Retrieved January 1, 2019.
  11. PMID 28559337
    .
  12. PMID 27881302
    .
  13. PMID 27087444
    .
  14. PMID 27662088
    .
  15. PMID 28092658
    .
  16. ^ "Feb 17, 2016: ISCB Congratulates 2016 Award Winners, Soren Brunak, Debora Marks, Burkhard Rost, and Serafim Batzoglou". www.iscb.org. Retrieved July 11, 2016.
  17. ^ "Chan Zuckerberg Science Initiative". Neurodegeneration Challenge Network. Archived from the original on December 31, 2019. Retrieved January 1, 2019.
  18. ^ "April 28, 2022: ISCB Congratulates and Introduces the 2022 Class of Fellows!". www.iscb.org. Retrieved June 17, 2022.

External links

Retrieved from "https://en.wikipedia.org/w/index.php?title=Debora_Marks&oldid=1198128865"