The Computational Informatics Research Laboratory (CiRL)

group focuses on fundamental and applied research in the life sciences domains. We design and develop applied computational methods for the understanding, analysis and integration of data primarily coming from multi-modal medical imaging modalities as well as multi-omics data. We also teach courses such as, medical image processing and bioinformatics (with a focus on data analysis) to students at the bachelor, master and PhD levels.

PROJECTS OF CiRL

  • Started in 2016

    Continued

    The knowledge of protein functions plays an essential role in understanding biological cells which have a significant impact on human life in areas, such as, personalized medicine, better crops and therapeutic interventions. The technological advancement in the field of biology is improving the level of biological information associated with proteins. A key issue that has received little or no attention is how to incorporate and take advantage from the ever evolving biological information in building effective models for protein function predictions. In this project, we will address this issue by examining proposing and analyzing predictive models suitable for this task.

  • Started in 2021

    Continued

    The Corona Virus Disease 2019 (COVID-19) is a lethal disease, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, which is affecting millions of people worldwide. Infected patients exhibit symptoms such as high fever, cough, shortness of breath etc. Currently, the gold standard test to detect COVID-19 is the real-time reverse transcription polymerase chain reaction (RT-PCR) test, while it is also an expensive, manual and time-consuming screening method. An alternative method used for the detection of COVID-19 disease is the visual examination of chest X-rays. Although the X-ray images provide good contrast for the presence of COVID-19 disease but their quality is often affected due to various factors, most importantly:

    1. Compton scattering
    2. Geometric un-sharpness

    These problems result in vague appearance of the opacities, as well as variability in the shape of the opacity in X-ray radiographs. To overcome these problems, this works conceptualizes the development of a constrained size, cascaded deep learning model that will improve the segmentation of lungs in the chest X-ray images, in order to improve the screening of COVID-19 disease.

Our Research Team

Research Papers

Journal Papers

Muhammad Touseef Irshad, Hafeez Ur Rehman Gradient Compass-Based Adaptive Multimodal Medical Image Fusion IEEE Access

IEEE,2021


Musadaq Mansoor, Mohammad Nauman, Hafeez Ur Rehman , and Alfredo Benso Gene Ontology GAN (GOGAN): A Novel Architecture for Protein Function Prediction

,2021


Debesh Jha, Zeshan Khan, Muhammad Atif Tahir, others A comprehensive analysis of classification methods in gastrointestinal endoscopy imaging Medical image analysis

Elsevier,2021


Asad Khan, Hafeez Ur Rehman, Usman Habib, Umer Ijaz Detecting N6-methyladenosine sites from RNA transcriptomes using random forest Journal of Computational Science

Elsevier,2020


Hafeez Ur Rehman, Asad Khan, Usman Habib Fog computing for bioinformatics applications Fog Computing: Theory and Practice

John Wiley and Sons Inc.,2020


Irshad Khan, Naveed Islam, Hafeez Ur Rehman, Murad Khan A comparative study of graphic symbol recognition methods Multimedia Tools and Applications

Springer US,2020


Hafeez Ur Rehman, Usman Habib, Umer Ijaz, Naveed Islam, Atta Ur Rehman Khan, Raheel Nawaz Identification of Yeast’s Interactome Using Neural Networks IEEE Access

IEEE,2019


Conference Papers

Zeshan Khan, Usman Tariq, Muhammad Atif Tahir, Shahbaz Memon Medical Diagnostic by Data Bagging for Various Instances of Neural Network Pattern Recognition. ICPR International Workshops and Challenges

Springer, Cham,2021


Syed Muhammad Faraz Ali, Muhammad Taha Khan, Syed Unaiz Haider, Talha Ahmed, Zeshan Khan, Muhammad Atif Tahir Depth-Wise Separable Atrous Convolution for Polyps Segmentation in Gastro-Intestinal Tract MediaEval

MediaEval,2020


Behraj Khan, Tahir Syed, Zeshan Khan, Muhammad Rafi Textual analysis of End User License Agreement for red-flagging potentially malicious software 2020 International Conference on Electrical, Communication, and Computer Engineering (ICECCE)

IEEE,2020


Omar Bin Samin, Maryam Omar, Musadaq Mansoor, Noman Naseeb, Samad Ali Shah, Aqil Amjad Khan IoT Based Time Triggered SPE Smart Switch for AC Appliances Control Innovations in Bio-Inspired Computing and Applications: Proceedings of the 11th International Conference on Innovations in Bio-Inspired Computing and Applications (IBICA 2020)

Springer Nature,2020


Safia Fatima, Hafeez Ur Rehman, Aizaz Sharif, Usman Habib Evaluation of Multi-Modal MRI Images for Brain Tumor Segmentation 2019 15th International Conference on Emerging Technologies (ICET)

IEEE,2019