Ala’ Al-Afeef

profilephoto

Ala’ Al-Afeef is a Data Analysis Scientist for the electron Bio-Imaging Centre (eBIC). He joined in November 2016 from the University of Glasgow.

Email: ala.al-afeef@diamond.ac.uk
Tel: +44 (0) 1235 77 8966

Key Research Area

Other Specialist Areas

  • Single particle analysis
  • Electron tomography
  • Cryo-EM automation
  • Technique development
  • Compressed sensing
  • Machine learning
Please Wait
  1. Research Expertise
  2. Biography
  3. Technical
  4. Publications
Research Expertise -

Current Research Interests

We are in the midst of a revolution in structural biology, with the use of electron microscopy increasing enormously since the method can now reveal atomic detail for macromolecular complexes. Given the excess demand already experienced at eBIC and the high cost of cutting-edge microscopes, it is important to provide the correct software tools to enable users to do the best possible experiments.

I am involved in the development of the software infrastructure at eBIC to deal efficiently with the massive output of image data from our microscopes. I am also working on the development of computational methods and autonomous software pipelines for rapid analysis of cryoEM data. The pipelines are greatly aimed to improve the user experience by a) automatic time-saving data processing b) provide real-time feedback to optimise experimental set-up and machine time, and c) ensure correct procedures are applied.
 
My research interest also includes a strong focus on image processing, machine learning. Other interests include: compressed sensing, tomography for material science and chemical mapping using DualEELS.

My role is focused on the analysis of Cryo-electron microscopy data to support users of eBIC at Diamond. My current project aims to automate the data processing of cryo-EM, to enable the on-line reconstruction of 3D structural information of biological molecules and assemblies. This ultimately aims to auto-process terabytes of images that are usually acquired in a typical cryo-ET session and to enable e-BIC users to speed-up the processing required by the computationally intensive Single particle (SPEM) and Electron microscopy (ETEM) routines.
 
 

 

Biography - +

Biography

Dr Al-Afeef is a computer scientist with a specialisation in electron microscopy. He currently works on data-processing development of single particle analysis and electron tomography based on Cryo-electron microscopy.

Ala' received his Ph.D. in computing science from university of Glasgow. He then carried out his post-doctoral work at the school of physics at university of Glasgow where he collaborated with the department of material in Oxford University. In 2016, he joined Diamond as a data analysis scientist.

His research is focused on improving the analysis of Cryo-EM data in order to advance the understanding of structure and functionality of viruses, cellular and molecular assemblies. Ala received many honours and awards, including the Lord Kelvin Adam Smith PhD scholarship from University of Glasgow in 2012-2016 and the 2014 young scientists award by the international federation of societies for microscopy (IFSM). Ala has been a member of the Royal Microscopical Society since 2012.

Technical - +

Technical

I have working experience with a variety of EM software packages including Relion, Scipion, Imod, PEET, AMIRA and Digital micrograph. Fluent in Python, C++, Matlab. Working knowledge in CUDA, MPI/OpenMP and Prolog programming. Experience in university teaching and technical training. I also have experience in using TEM microscopes (JEOL ARM200cF and FEI Tecnai T20).

Publications - +

10 most recent publications

  1. Ala Al-Afeef, W.Paul Cockshott, Ian MacLaren, and Stephen McVitie. Electron tomography image reconstruction using data-driven adaptive compressed sensing. Journal of Scanning Microscopies, 38(3), 2016.
    doi: 10.1002/sca.21271
     
  2. Ala Al-Afeef, Joanna Bobynko, W Paul Cockshott, Alan J Craven, Ian Zuazo, Patrick Barges, and Ian MacLaren. Linear chemically sensitive electron tomography using dualeels and dictionary-based compressed sensing. Ultramicroscopy, 107:96−106, 2016.
    doi: 10.2016/j.ultramic.2016.08.004
     
  3. Alexander Alekseev, Gordon J Hedley, Ala Al-Afeef, Oleg A Ageev, and Ifor DW Samuel. Morphology and local electrical properties of PTB7:PC71 BM blends. Journal of Materials Chemistry A, 3(16):8706−8714, 2015.
    doi: 10.1039/C5TA01224D
     
  4. Ala Al-Afeef, W.Paul Cockshott, and Ian MacLaren. Dictionary based reconstruction of the 3D morphology of ebola virus. In Microscopy and Microanalysis MM2015, 21(S3): 905−906, 2015.
    doi: 10.1017/S1431927615005322
     
  5. Ala Al-Afeef, W. Paul Cockshott, Patrick Barges, Ian Zuazo, Joanna Bobynko, Alan J. Craven, and Ian Maclaren. Linear chemically sensitive electron tomography using DualEELS and compressed sensing. Microscopy and Microanalysis, 21(S3): 2341−2342, 2015
    doi: 10.1016/j.ultramic.2016.08.004
     
  6. Ala Al-Afeef, P Cockshott, I MacLaren, and S McVitie. Compressed Sensing Electron tomography using adaptive dictionaries: a simulation study. J.Phys.: Conf. Ser., 522(1):012021, June 2014.
    doi: 10.1088/1742-6596/522/1/012021
     
  7. Ala Al-Afeef, Alexander Alekseev, Gordon J Hedley, Ifor DW Samuel, Cockshott Paul, MacLaren Ian, and McVitie Stephen. Electron tomography of ptb7:pc70bm. In IMC2013, Prague, Czech Republic, 2014.
    doi: 10.13140/2.1.3327.7762
     
  8. Sheta, Alaa F., Peter Rausch, and Ala Al-Afeef. A monitoring and control framework for lost foam casting manufacturing processes using genetic programming. International Journal of Bio-Inspired Computation 4.2 (2012): 111-118.
    doi: 10.1504/IJBIC.2012.047182
     
  9. Sheta, Alaa F., Peter Rausch, and Ala Al-Afeef. Quality Management Using Electrical Capacitance Tomography and Genetic Programming: A new Framework. Research and Development in Intelligent Systems XXVIII. Springer London, 2011. 211-216.
    doi: 10.1007/978-1-4471-2318-7_15
     
  10. Alaa Sheta, Ala Al-Afeef, Software Effort Estimation for NASA Projects Using Genetic Programming. Journal of Intelligent Computing, Volume 1. Number. 3, pp. 146-156, April 2010.