Amjad Ali, is the head of Integrative Biology Laboratory (iBG) and Microbial Genomics and Bioinformatics (MGB) research group, He is Tenured Professor at Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST) since 2013.
My broader research interests combine interdisciplinary work in antimicrobial peptides (AMPs) aand comparative genomics, using bioinformatics and large genomic datasets to understand how microorganisms acquire resistant genes and to identify candidate genes that can be targeted for therapeutic interventions.
My research interest includes the integration of Artificial Intelligence in Microbial Genomics Research. I aim to apply Machine Learning and Deep Learning methodologies to huge heterogeneous high-throughput sequencing data to perform genomics tasks, in order to accelerate novel discoveries in the area of genomics and precision medicine.
I am a Microbiologist by background, I joined MGB in 2018 as a master’s student, and ever since then I worked enthusiastically on various projects. Currently, as a PhD candidate, I am aiming on developing a poultry vaccine against colibacillosis-a systemic infection in chickens that causes high mortality and morbidity. I am employing reverse vaccinology and pangenomics to identify and prioritize potential vaccine candidates, as well as the molecular cloning, expression and purification of these candidate vaccines, and their immunogenicity evaluation in chicken models.
My research focuses on Machine Learning & Deep Learning-based Microbial Genomics and Comparative Genome Analysis. Python programming, Back-end & Front-end development, website development, and creative designing are my major skills. As a Masters Scholar in iBG, I’ve developed Machine Learning-based Reverse Vaccinology model for effective predictions of bacterial vaccine candidates in ESKAPE pathogens, which can be used to develop vaccines to combat nosocomial & community-acquired infections. I am currently employed as “Research Assistant” in HEC NRPU project entitled “An Artificial Intelligence Framework for Data Driven Analysis of Microbial Pangenomes “ in ASAB under Principal Investigator (PI) of project Dr. Amjad Ali.
I have Bachelors degree in Applied Biosciences and I am coder by passion who love to learn new things. I have joined IBG in 2021 as an intern and acquired hands-on-training on a number of tools and techniques used in biological data analysis. My FYP project was focused on the development of a real-time database of antimicrobial peptides i.e., rtAMPs. I have expertise in R statistical programming language ,Python, Backend and Frontend development and I want to utilize all my computational skills to solve biological problems. I am currently employed as “Research Assistant” in HEC NRPU project entitled “An Artificial Intelligence Framework for Data Driven Analysis of Microbial Pangenomes “ in ASAB under Principal Investigator (PI) of project Dr. Amjad Ali.
Biochemistry graduate of 2023 seeking continuous learning. Interned at iBG in 2022 and 2023, gaining hands-on training in various biological data analysis tools. My research interests span comparative genomics and reverse vaccinology through interdisciplinary approaches, employing cutting-edge bioinformatics tools.
My project was focused on comparative microbial genome analysis and bioinformatics software designing. In my current project, I am developing a software pipeline named ‘PanRV’. This pipeline is designed to identify putative vaccine candidates from multiple prokaryotic genomes (Pangenome) for vaccine development against pathogenic bacterial species. The pipeline provides the Graphical User Interface (GUI) for the ease of biologists. It is a Linux-based package available at https://sourceforge.net/projects/panrv2/. Here, we also provided the User guide and an automatic installer for easy installation of the pipeline.
My broader research interests combine interdisciplinary work in molecular microbiology and comparative genomics, using bioinformatics and large genomic datasets to understand how microorganisms acquire resistant genes and to identify candidate genes that can be targeted for therapeutic interventions. My Ph.D. project focuses on the gram-positive bacterial pathogen (opportunistic) Staphylococcus aureus; to understand how antimicrobial resistance spreads via mobile elements as well as repeated independent acquisitions of intrinsic mechanisms through changes in the chromosome. My research also focuses on molecular cloning, expression, and purification of multi-epitope recombinant vaccine candidates and their immunogenicity evaluation in a mouse model. Publications can be accessed online: PMID: 34572703; PMID: 31557564; PMID: 35341759; PMID: 35453247. Proceeding for Postdoctoral Training at Indiana University, USA.
Dr. Anam is a bioinformatician by her expertise. She has completed her PhD in Applied Biosciences with specialization of bioinformatics and computational Biology. Her research work focuses on the identification and prioritization of potential vaccine candidates employing reverse vaccinology, pan genomics, pathway analysis, host pathogen interactions, systems biology and data analysis. Recently she has been working on prioritizing vaccine candidates against SARS-CoV-2. Her other expertise includes NGS data analysis, data mining, coding and scripting for genome and proteome analysis to reveal potential therapeutic targets. She is an active faculty member @ University of Lahore and along with research she is also teaching under graduate and postgraduate courses.
My PhD work focused on the modeling and analysis of innate immune responses induced by the host cells against Hepatitis C Virus infection. A simplified formalization of the highly dynamic system consisting of HCV, its replication cycle and host immune responses at the cellular level using Hybrid Petri Net (HPN) was presented. In this study in order to understand the mechanisms involved in immune evasion by HCV. Our model also provides some biological insights regarding the role of PKR in the acute infection of HCV. I am Currently working as an Assistant Professor @ University of Haripur, Khyber Pakhtunkhwa.
Dr. Tariq Saeed is an Associate Professor at the School of Inter-disciplinary Engineering and Sciences (SINES) NUST. He has completed his Ph.D. under the co-Advisory of Dr. Amjad Ali. He is an active team member contributing to the modeling and simulation of biological systems, machine learning, and artificial intelligence-related projects, co-supervising student research projects related to ML-based models for vaccine candidates’ predictions. He is also Co-PI in a funded project “An Artificial Intelligence Framework for Data-Driven Analysis of Microbial Pangenomes”.
Dr. Rehan’s core research interests involves signalling pathways and computational system level approaches o get insights into the mechanism of disease progressions. As PhD scolar at IBG he done a thesis on “Modelling of TLR4 and JAK/STAT Signalling Pathways and Protein-Protein Interaction Studies to Examine the Patho-physiology of Sepsis”
Hamza Arshad Dar’s research was focused on microbial pan-genome analysis, subtractive proteomics, structural bioinformatics, reverse vaccinology and computer-aided drug design. During his stay at NUST, he mainly focused on exploring pathogenic microorganisms, including bacteria (Klebsiella pneumoniae, Mycobacterium tuberculosis) and viruses (SARS-CoV-2) for the identification of putative drug targets, and antigenic epitopes for designing multi-epitope based subunit vaccine. He also contributed towards another project on comparative genome analysis of a new sequence type (ST5352) methicillin-resistant Staphylococcus aureus (MRSA) strain with other global MRSA strains, to explore antimicrobial resistance and virulence. So far, he has published research work in international journals such as Vaccines (MDPI), Scientific Reports (Nature), PeerJ, and Infection, Genetics and Evolution (Elsevier). Hamza was a student in NUST from 2013 to 2019, and is currently pursuing a doctoral degree in Bioinformatics at KAIST, South Korea.
Muhammad Shehroz has obtained his Master’s degree in Industrial biotechnology from NUST Islamabad. He is pursuing research in the area of Microbial Genomics, Comparative genomics, drug discovery, and Reverse vaccinology. During his research work, he worked on secondary metabolites prediction from pseudomonas fluorescence to predict useful compounds that have therapeutic effects. He also worked on whole-genome sequencing and comparative genome analysis, in order to design vaccine candidates and predict potential drug targets for a multi-drug Resistant Staphylococcus haemolyticus, a pathogenic bacteria that cause nosocomial infections. He has published 13 research articles in highly reputed international journals and also contributed to two book chapters. Muhammad Shehroz worked as a Research Assistant from 2018-2019 at IBG and is currently working as Lecturer in Bioinformatics @ Kohsar University, Murree.
Fatima Shahid joined IBG in 2017 as a Master’s student. She worked on bacterial genome analysis: Pangenome and comparative bacterial genomic analysis all the way from genomic and proteomic data retrieval, processing and prediction of therapeutic targets. She has used the in-house piplelines such as VacSol (vaccine prediction target prediction) and PanRV for pangenome and reverse vaccinology. She has also used a similar workflow to predict potential vaccine candidates against SARS-COV-2. The work has resulted in interesting data which have been published in well reputed journals. She is currently serving as a graduate research assistant and pursuing her PhD in “structural Bioinformatics” at Universiti Kebangsaan Malaysia.
My interests and aims revolves around computational vaccine designing, against one of the ESKAPE pathogen “Enterococcus faecium” using bioinformatics and in silico techniques of pangenomics and reverse vaccinology i identified potential vaccine candidates and further validations and in silico immunogenicity evaluations of these vaccine candidates is under way. I am currently employed at Shifa International Hospital Islamabad.
I am Amina and research interest combines the interdisciplinary work that includes pan-genome analysis, drug discovery, drug target identification specifically against one of ESKAPE pathogen Acinetobacter baumannii using bioinformatics, and a large genomic dataset for alternative therapeutic intervention. The lead optimization and its experimental validation can provide a strong foundation to develop safe and potential drugs against Acinetobacter baumannii related infection.
A spreadsheet containing data of internees who gained hands-on training on research projects at IBG lab.
Integrative Biology Laboratory, Atta-ur-Rahman School of Applied Biosciences (ASAB)
1st floor, D Block, National University of Sciences and Technology (NUST, H-12 Islamabad.
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