Giuseppe Narzisi

Starting May 1st 2014 I have joined the Bioinformatics Group at the New York Genome Center (NYGC). My new home page can be found here.
Short Bio

I am currently a Computational Science Analyst I at the Simons Center for Quantitative Biology (SCQB) of Cold Spring Harbor Laboratory (CSHL) where I am working with Professor Michael Schatz to develop novel algorithms and computational systems to analyze DNA sequences, concentrating on the assembly and alignment of next generation sequencing reads. Applications include analysis of genetic variations in human genome to identify the genetic causes of various human diseases including autism, cancer, and other psychiatric conditions. Before this position, I was appointed as a Research Scientist at the NYU Bioinformatics Group of Courant Institute of Mathematical Sciences (CIMS) where, together with Professor Bud Mishra, I developed novel sequence assembly and base-calling methods for next generation sequencing data. I received a Ph.D. in Computer Science from New York University (NYU) in 2011 and from University of Catania (UniCT) in 2008 respectively. I have been awarded an IBM PhD Fellowship for the 2010-2011 academic year.

Check out my CV for more details.
Here you can find my old home page at NYU.

Research Interests

Thanks to the enormous advances in DNA sequencing technology there is now the potential to perform analyses that can be directly applied to many different areas in Computational Biology such as, genome-wide association studies, detecting new polymorphisms, finding rare and de novo mutations. However the availability and performance of the computational tools required to analyze these data continue to lag far behind the improvements in technology. To address this issue, my research has focused on designing an developing new techniques and algorithms for different Computational Genomics problems. In particular my main areas of research are: Variant Calling, Genome assembly, Base-Calling, and Assembly Validation for Next-Generation sequencing technology. I previously worked in: Protein Structure Prediction, Multi-objective Optimization, Evolutionary Computation and Multi-Agent Systems.

Seminars and Lectures

Towards accurate germline and somatic indel discovery with Micro-Assembly
New York Genome Center (NYGC) USA, February 2014.
Micro-assembly approach to discover INDELs in NGS data
Computational Biology & Bionformatics seminar. Simons Center for Quantitative Biology (CSHL) USA, November 2013.
SCALPEL - Micro-assembly approach to detect INDELs within exome-capture data
Genome Informatics 2013, (GI2013), USA, October 30 - November 2, 2013.
Discovering Indels within Human Exome-Capture data
Quantitive Biology Seminar Series 2012, Cold Spring Harbor Laboratory (CSHL) USA, September 2012.
From DNA Sequencing to Genomes: the Assembly Challenge
2nd Conference on Systems Biology and New Sequencing Techniques (SBNST): The Abdus Solam International Centre for Theoretical Physics (ICTP) Miramare - Trieste, Italy, October 2011.
From Sequencing to Sequences: Algorithms and Metrics for Accurate Genome Assembly
SchatzLab: Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory (CSHL) USA, August 2011.
SUTTA: Scoring-and-Unfolding Trimmed Tree Assembler
Zhang Lab: Computational Biology and Bioinformatics, Cold Spring Harbor Laboratory (CSHL) USA, September 2009.
A Multi-Objective Evolutionary Approach to the Protein Structure Prediction Problem
Computer-Aided Systems Laboratory (CASL), Princeton University USA, December 2007.

Faculty of 1000 Reviews

SOAPindel: Efficient identification of indels from short paired reads.
Li, S. et al. (2012) Genome Research. Nov 27.
De novo assembly and genotyping of variants using colored de Bruijn graphs.
Iqbal Z et al. (2012) Nat Genet. 44(2):226-32

Selected Publications (see more in Google Scholar)

Narzisi G., O'Rawe J.A., Iossifov I., Fang H., Lee Y., Wang Z., Wu Y., Lyon G.J., Wigler M., Schatz M.C.
Accurate detection of de novo and transmitted INDELs within exome-capture data using micro-assembly. CSHL bioRxiv (DOI: 10.1101/001370)
Ming R., VanBuren R., Liu Y., Yang M., Han Y., Li L., Zhang Q., Kim M, Schatz M., Campbell M., Li J., Bowers J., Tang H., Lyons E., Ferguson A., Narzisi G., Nelson D., Blaby-Haas C., Gschwend A., Jiao Y., Der J., Zeng F., Han J., Min X.J., Hudson K., Singh R., Grennan A., Karpowicz S., Watling J., Ito K. et al.:
Genome of the long-living sacred lotus (Nelumbo nucifera Gaertn.). Genome Biology, 2013, 14:R41. (DOI: 10.1186/gb-2013-14-5-r41).
Vezzi F., Narzisi G., and Mishra B.:
Reevaluating Assembly Evaluations with Feature Response Curves: GAGE and Assemblathons. PLoS ONE 2012, 7 (12): e52210 (DOI: 10.1371/journal.pone.0052210).
Iossifov I., Ronemus M., Levy D., Wang Z., Hakker I., Rosenbaum J., Yamrom B., Lee Y., Narzisi G., Leotta A., Kendall J., Grabowska E., Ma B., Marks S., Rodgers L., Stepansky A., Troge J., Andrews P., Bekritsky M., Pradhan K., Ghiban E., Kramer M., Parla J., Demeter R., Fulton L.L., Fulton R.S., Magrini V.J., Ye K., Darnell J.C., Darnell R.B., Mardis E.R., Wilson R.K., Schatz M.C., McCombie R.W., Wigler M.:
De novo gene disruptions in children on the autism spectrum. Neuron. 74:2 285-299, 2012. (DOI: 10.1016/j.neuron.2012.04.009).
Vezzi F., Narzisi G., and Mishra B.:
Feature-by-Feature - Evaluating De Novo Sequence Assembly. PLoS ONE 7(2): e31002, February 2012. (DOI: 10.1371/journal.pone.0031002).
Schatz M. C., Phillippy A. M., Sommer D., Delcher A. L., Puiu D., Narzisi G., Salzberg S. L., Pop M.:
Hawkeye and AMOS: visualizing and assessing the quality of genome assemblies. Briefings in Bioinformatics, December 2011. (DOI: 10.1093/bib/bbr074).
Narzisi G. and Mishra B.:
Comparing De Novo Genome Assembly: The Long and Short of It. PLoS ONE 6(4):e19175. April 2011 (DOI: 10.1371/journal.pone.0019175).
Narzisi G. and Mishra B.:
Scoring-and-Unfolding Trimmed Tree Assembler: Concepts, Constructs and Comparisons. Bioinformatics, Oxford Journals, (2011) 27 (2): 153-160 (DOI: 10.1093/bioinformatics/btq646).
[Revision, Feb 10 2011]
Menges F., Narzisi G., and Mishra B.:
TotalReCaller: Improved Accuracy and Performance via Integrated Alignment & Base-Calling. Bioinformatics, Oxford Journals, (2011) 27(17): 2330-2337 (DOI: 10.1093/bioinformatics/btr393).
Smith S.W., Portelli I., Narzisi G., Nelson L.S., Menges F., Rekow E.D., Mincer J.S., Mishra B., Goldfrank L.R.:
A Novel Approach to Multi-Hazard Modeling and Simulation. Disaster Medicine and Public Health Preparedness (DMPHP), The American Medical Association (AMA), 2009 (DOI: 10.1097/DMP.0b013e3181a88899).
Cutello V., Narzisi G., Nicosia G.:
A Multi-Objective Evolutionary Approach to the Protein Structure Prediction Problem. Journal of the Royal Society Interface, Royal Society Publications London, vol. 3, issue 6, pp. 139-151, 22 February 2006 (DOI: 10.1098/rsif.2005.0083).
Anile A.M., Cutello V., Narzisi G., Nicosia G., Spinella S.:
Determination of protein structure and dynamics combining immune algorithms and pattern search methods. Natural Computing Int. Journal, Springer 2006 (DOI: 10.1007/s11047-006-9027-3).

Reviewer for

Bioinformatics, Oxford Journals.
Proceedings of the Royal Society B: Biological Sciences, International Journal.
BMC Bioinformatics, International Journal.
PLOS ONE, International Journal.
Nucleic Acids Research, Oxford Journals.
Robust Intelligence (RI) Division of Information and Intelligent Systems (IIS) at the National Science Foundation (NSF).
IEEE Transactions on Evolutionary Computation. International Journal.
Natural Computing. International Journal, Springer.
Journal of Mathematical Modelling and Algorithms, Springer.
Information Sciences, International Journal, Elsevier.
Knowledge-Based Systems, International Journal, Elsevier.
Memetic Computing, International Journal, Springer.

Giuseppe Narzisi, Ph.D.
Cold Spring Harbor Laboratory
One Bungtown Road
Koch Building 1121
Cold Spring Harbor, NY 11724

E-mail: gnarzisi <at> cshl.edu
Phone: (516) 367-5244