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Mario Messih

Personal Contact

Full Name:                          Mario Alfy Fahmy AbdelMessih

Current address:                 Viale Carlo Felice, 63, B2, 00185 Roma, Italy

Permanent Address:           Ramsis St, Naseem Salama Building, Second Floor,85952 Luxor, Egypt

Date of Birth:                       Sept, 1988

Citizenship:                          Egyptian

Mobile:                                 +39-380-797-9710

Email:                                  marioabdelmessih@gmail.com, mario.messih@kaust.edu.sa

Skype:                                 mario.alfy

 

Research Interests

Machine Learning, Data Mining, Artificial Intelligence, Bioinformatics, Structural Biology, Protein Structure and Function, Antibody Structure.

Education


PhD in Life Sciences, Sapienza University of Rome, Physics Department, Italy.
Thesis: Predicting protein loops using machine learning techniques.

 

Jan, 2016 (expected)
MS in Computer Science (Bioinformatics), King Abdullah University of Science and technology (KAUST), KSA. (GPA: 3.6/4.0 ”honor list”)
 Thesis: A New Outlier Detection Method for Multidimensional Datasets with application to Redundancy Reduction.
 Supervisor: Professor Vladimir Bajic.

July, 2012
BS in Computer Science, The American University in Cairo (AUC), Egypt. (GPA: 3.6/4.0”Dean’s list”).
Thesis: Real Time, Multi-object Tracking System Using GPU with application to Interactive Gaming.
Supervisor: Professor Joshua Gluckman.
July,2010
             
   

Technical Skills


Professional: R – C/C++ - MATLAB.
BASIC: Python – Perl – Java – Hadoop – HTML – XML .
OS: Linux – Windows – OSX.
Languages: English – Arabic.
Softwares: Pymol – Modeller – Biopython – BLAST – HMMER – LGA – CD Hit.


Publications


                                                                            Journal Articles

   [1] Messih MA, Chitale M, Bajic V, Kihara D and Gao X. Protein domain recurrence and order can enhance prediction of protein functions. (2012) Bioinformatics 28(18) i444-i450.

   [2] Messih MA,  Lepore R, Marcatili P, Tramontano A. Improving the accuracy of the structure prediction of the third hypervariable of the heavy chain of antibodies.  (2014) Bioinformatics 30(19) 2733-40.

                                                                              Conferences

    M. Messih, M. Chitale, V. Bajic, D. Kihara and X. Gao. Protein domain recurrence and order can enhance prediction of protein functions. The 11th European Conference on Computational Biology (ECCB2012). Basel, Switzerland, September 2012.  (Acceptance rate 14%).

                                                                                   Posters

    [1] Messih MA, Lepore R, Marcatili P, Tramontano A. Structure prediction of antibody hypervariable H3 loops using random forest. (2014) Societa di Bioinformatics Italiana (Bits annual meeting).
    [2] Messih MA, Lepore R, Marcatili P, Tramontano A. Improving the accuracy for the structure prediction of antibody hypervariable H3 loops using random forest. (2015) Biology and Molecular Medicine symposium (BEMM annual meeting).
PhD in Life Sciences, Sapienza University of Rome, Physics

Department, Italy.

- Group: The Biocomputing Group (www.biocomputing.it ).

- Thesis: Predicting protein loops using machine learning

techniques.

- Supervisor: Professor Anna Tramontano.

MS in Computer Science (Bioinformatics), King Abdullah

University of Science and technology (KAUST), KSA. (GPA:

3.6/4.0 ”honor list”)

- Group: Computational Bioscience Research Center (CBRC)

(www.cbrc.kaust.edu.sa ).

- Thesis: A New Outlier Detection Method for Multidimensional

Datasets with application to Redundancy Reduction.

- Supervisor: Professor Vladimir Bajic.

BS in Computer Science, The American University in Cairo

(AUC), Egypt. (GPA: 3.6/4.0”Dean’s list”).

- Thesis: Real Time, Multi-object Tracking System Using GPU

with application to Interactive Gaming.

- Supervisor: Professor Joshua Gluckman.
Last Updated ( Thursday, 16 April 2015 12:11 )