Daniel P. Aalberts

Professor of Physics

at Williams since 1997

Contact Information


2017-2018 Courses

Courses given previously

Research interests

Biological polymers, studied with statistical and computational physics techniques.

Optimizing gene expression with mRNA free energy modeling and algorithms

The same protein sequence can be encoded by many different mRNA sequences because of the degeneracy of the genetic code. Variations in mRNA sequence can play an important role in regulating protein expression level; for example, synonymous mutations may alter human susceptibility to diseases. We seek to understand the RNA features controlling gene expression. Analyzing protein expression experiments performed by the Northeast Structural Genomics (NeSG) Consortium, we find that mRNA folding effects dominate in the head region (initial 16 codons), while codon usage dominates in the tail (the remainder). Head and tail have similar overall influence. press release
[Supported by a grant from the National Institutes of Health (GM106372)]

Binding and Splicing mRNA

The famous double helical shape of DNA arises when the bases of the two complementary strands pair. Base-pairing is also the key to allowing special sites of mRNA to be recognized and we have developed a tool BINDIGO to efficiently calculate free energies to optimally BIND olIGOs (short pieces) of RNA to long RNA, important for mRNA splicing, siRNA, miRNA, etc. To predict mRNA splice sites, we have used physical chemical models (Finding with Binding) and a novel statistical method (Primary Sequence Ranking).
[Supported by a grant from the National Institutes of Health (GM080690)]

Improving RNA Pseudoknot Models and Algorithms

RNA is more than an intermediary between DNA and proteins, it also modulates gene expression and catalyzes certain reactions. Complementary base pairing condenses RNA into complex, compact shapes. Hairpin or tree-like structures (Fig a) emerge most often, but occasionally the more complicated pseudoknot fold (Fig b) appears.

Pseudoknots are not common, but have amazing functionality when they do appear, catalyzing reactions as enzymes or performing other gene regulation functions. For example, the core of most catalytic RNAs is the interesting pseudoknot fold. Pseudoknots cannot be predicted using traditional RNA folding algorithms. Aalberts and his students have been improving models of pseudoknot structures and have been computing how abundant pseudoknots are.
[Supported by a grant from the National Science Foundation (MCB 0641995)]

The figures depict the molecular backbone and the base pairs.

Physics of Vision:

Rhodopsin, the optically active molecule in our eyes, changes shape when it absorbs a photon. This is the fastest photochemical reaction known --- 200 femtoseconds, less than the time it takes light to cross the width of your hair. Rhodopsin is a highly efficient system with very little noise which is one of the reasons we see when our rod cells are stimulated by only a few photons. I have been developing quantum mechanical models to study how absorption of light creates compact, coherent excitations called solitons and how these may induce the molecular shape change.
[Supported with a Cottrell College Science Award by the Research Corporation]

Selected publications

Thesis Students

  • Brian Gerke '99
    [Apker Award for best US undergrad physics research,
    MPhil '01 Cambridge Univ (UK),
    Ph.D '07 Berkeley, Lawrence Berkeley Lab]
  • Jonathan Pyle (Swarthmore '99) [J.D., lawyer in Pennsylvania]
  • Ben Cooper '01 [Ph.D Maryland, now Calico Life Sciences]
  • Fritz Stabenau '02 [Ph.D '08 UPenn., M.D. '16 Yale]
  • John Parman '02 [Ph.D '08 Northwestern Econ.,
    Prof at William and Mary]
  • Jeff Garland '03 [Cambridge Univ (UK),
    Harvard Law School]
  • Nathan Hodas '04
    [Apker Award for best US undergrad physics research,
    Ph.D '11 Caltech, now Pacific Northwest National Lab]
  • Eric Daub '04 [Ph.D '09 UCSB, Prof at Univ Memphis]
  • Rob Cooper '06 [Ph.D '12 Princeton]
  • Alex Zaliznyak '07 [Econ Ph.D student at Stanford]
  • Sandy Nandagopal '09 [Caltech Ph.D program]
  • Becca Sullivan '11 [Teaching Fellow, NYC]
  • Jeff Meng '11 [Harvard MD-Ph.D program]
  • Joel Clemmer '12 [Johns Hopkins Biophys Ph.D program]
  • Julian Hess '13 [Broad Institute]
  • Mike Flynn '15 [Analyst, Hutchin Hill Capital; then Caltech PhD]
  • Bijan Mazaheri '16 [Cambridge Univ (UK), Caltech PhD]
  • Daniel Wong '17 [Cambridge Univ (UK)]
  • Intekhab Hossain '17 [Analyst, Analysis Group Boston]
  • Niki Howe '17 [Cambridge Univ (UK)]
  • Eliza Matt '18

Research Students

Scientific Programmer


Curriculum Vitae

Williams Physics