Kourosh Zarringhalam

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Contact Info

Kourosh Zarringhalam
Biology Department
Boston College, Higgins Hall 420A
140 Commonwealth Ave, Chestnut Hill, MA 02467
kourosh.zarringhalam [AT] bc [DOT] edu

I am a postdoctoral research fellow in Computational Biology with the Chuang lab here at BC. I obtained my PhD in Mathematics from the University of New Hampshire. Please click here for a copy of CV.


Research Interest

I am interested in the application of computational algorithms and mathematical models in biological systems. I am actively working in the following areas:

High Throughput Lipidomics

Lipidomics is a rapidly emerging field, requiring more advanced integration of mathematical and computational approaches to interpret accruing datasets of complex distributions of lipidmolecular species. I am interested in developing mathematical and computational models to infer the complex network of acyl chain interactions and the remodeling pathway of phospholipids.

RNA secondary structure

I am currently collaborating with Clote Lab in developing novel algorithms for improving the prediction of RNA secondary structure. We have developed a novel method to integrate chemical or enzymatic footprinting data (e.g. SHAPE, PARS, in-line probing, etc.) into thermodynamics-based RNA secondary structure algorithms. I am extending this algorithm to include the information from RNA "mutate-and-map" experiments developed by Das Lab.

Gene Regulation

MicroRNAs are short endogenous RNAs that regulate gene expression post-transcriptionally. I am working on development of novel algorithms for the discovery of miRNAs and their targets, in particular in coding sequences.

Computer Vision and Behavioral Analysis

During 2009-2010 academic year, I worked with Oliver King at the Boston Biomedical Research Institute BBRI where I developed a computer vision based software and statistical models for automatic quantification of mouse home-cage behaviors, suitable for continuous 24hr video monitoring. We validated our program by assessing behavioral changes in the R6/2 transgenic mouse model of Huntington’s disease over a ten-week period. I am working on integrating more machine learning algorithms into our software for detection of more complex behaviors.

Software Development


openCage is an open source computer vision based software developed in C++ for quantifying mouse home-cage behaviors.


RNAsc is an open source software written in C++ that uses chemical probing data and determines the RNA secondary structure with very high accuracy.


microBF is a software package written in python that uses a SVM classifier, trained on the Boltzmann Features of the pre-miRNA hairpin to detect novel MicroRNAs.


  1. Dynamics of the ethanolamine glycerophospholipid remodeling network, under revision.
  2. Integrating chemical footprinting data into RNA secondary structure prediction, In Press, PLoS ONE.
  3. Statistical analysis of processes controlling choline and ethanolamine glycerophospholipids molecular species composition, PLoS ONE, 2012.
  4. An open system for automatic home-cage behavioral analysis and its application to male and female mouse models of Huntington’s disease, Behavioural Brain Research, 2012.
  5. Sequential Adaptive Compressed Sampling Via Huffman Codes, Sampling Theory in Signal and Image Processing, 2011. http://arxiv.org/abs/0810.4916
  6. Nonlinear Least Squares in RN, Acta Applicandae Mathematicae, 2009.
  7. Compressed sampling via Huffman codes, Proceedings of the 2009 International Conference on Sampling Theory and Application SAMPTA09, 2009.
  8. Generating an adaptive multiresolution image analysis with compact cupolets, Journal of Nonlinear Dynamics, 2007.

Work Under Progress

  1. RNA secondary structure prediction using two-dimensional SHAPE data.
  2. microBF, a MicroRNA identification algorithm using Boltzmann triplet features.
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