GMEResearch

The GMEResearch Group achieved an outstanding milestone at the Career Expo 2025 at Capital University of Science & Technology by securing all top three positions. The first position was awarded to the team of Sarah Tariq, Rida Fatima, and Meezab Haider. The second position was secured by Wajeeha Javaid, Fatima Zahra, and Ayesha Wajid, while the third position was claimed by Quratul-Ain, Masooma Zahra, and Muneeba Rasheed. This exceptional achievement, accomplished under the supervision of Dr. Sayeda Marriam Bakhtiar, highlights the GMER Research Group’s strong commitment to applied research, innovation, and academic excellence.

Team GMER extends warm New Year wishes to everyone, hoping the year ahead brings continued innovation, strong collaboration, and meaningful, impactful research that advances knowledge and inspires progress together.

The Genetic and Molecular Epidemiology Research Group proudly announces the publication of the feature “The Gut-Brain Stress Connection: Surviving Exam Season” in Daily The Spokesman (26 November 2025 Edition). Authored by Ms. Fatima Zahra, the article highlights groundbreaking insights into how stress impacts gut–brain communication—especially during demanding academic seasons.

The GMEResearch Group Lead, Dr. Syeda Marriam Bakhtiar, delivered a distinguished keynote address at the 15th International Biennial Conference of the Pakistan Society for Microbiology (FIBC-PSM 2025), held on April 17, 2025, at Quaid-i-Azam University, Islamabad.

Dr. Bakhtiar’s keynote, titled “Unraveling the Microbiome–Metabolite Axis in Metabolic Syndrome via Integrative Metagenomics,” was featured in the thematic session on Microbial Virulence and Metabolism, chaired by Prof. Dr. Javed Asad. Her presentation highlighted the group’s cutting-edge research on microbiome dynamics and metabolic disease, showcasing significant contributions by Ms. Sahar Safdar.

The GMER Research Group celebrates this milestone as a testament to its commitment to advancing microbiome science, genomic innovation, and high-impact biomedical research in Pakistan.

A new review by GMER sheds light on the transformative role of Remote Patient Monitoring (RPM) in the management of cardiovascular diseases (CVDs). With heart-related disorders continuing to rank among the leading causes of death worldwide, this research emphasizes how digital health technologies are reshaping timely diagnoses, symptom tracking, and therapeutic interventions for cardiac patients. Wearable and implantable devices, real-time monitoring tools, and smart data analytics together provide a framework for proactive and accessible cardiac care.

The review also highlights how non-invasive and invasive monitoring systems, including pacemakers, implantable defibrillators, and wearable cardiac trackers, support both continuous assessment and early detection of complications. Machine learning-driven risk identification allows healthcare professionals to intervene before emergencies arise, significantly reducing hospitalizations, costs, and overall disease burden. These innovations empower patients with improved self-management while giving clinicians actionable insights for personalized treatment.

Despite the promise of RPM, the study underscores major implementation barriers in developing countries, especially the lack of ICT infrastructure, limited device accessibility, and inconsistent power supply. The authors call for strategic investment in technology, standardized protocols, and workforce training to strengthen digital health ecosystems globally. By addressing these challenges, RPM can become a cornerstone of equitable, efficient, and accessible care for cardiac patients.

Authors: Syeda Marriam Bakhtiar, Ayesha Aftab, Syeda Eeman Zahra Bokhari, Hajra Qayyum, Iqra Riasat, Amir Qayyum

Read more: https://www.eurekaselect.com/article/151424

Our latest study from the Genetic and Molecular Epidemiology Research (GMER) Group explores the interconnected landscape of MDD symptoms using association rule mining, decision tree classification, and agglomerative clustering.

This computational approach uncovers hidden co-occurrence patterns—such as the link between aggression and euphoric responses, and overthinking with euphoria—while identifying mood swings as a key predictive node for MDD.

Through cluster-based symptom mapping, the research emphasizes improved diagnostic precision and opens pathways for personalized therapeutic strategies.

Authors: Sahar Safdar, Abdur Rauf, Aneeza Zaheer, Zeenat Fatima, Syed Haseeb Ahmad Shah, and Syeda Marriam Bakhtiar

🔗 Read the full study here: https://njns.nust.edu.pk/index.php/njns/article/view/272/184

GMEResearch Group proudly showcased its research under the supervision of Dr. Syeda Marriam Bakhtiar at the 13th International Conference on Biological and Computational Sciences (C-BICS 2025) held at Capital University of Science and Technology (CUST) on 1 November 2025. Our team presented six research posters and three oral presentations, highlighting our work in Artificial Intelligence & Machine Learning, Molecular Biology, Metagenomics, and Mendelian Randomisation. This achievement reflects GMER’s continued commitment to advancing scientific research and fostering impactful collaborations.

GMEReseach Get together and Annual Lunch

www.gmeresearch.move.pk

AutoMode 1.0 (Protein modelling automated Software )

AutoMode 1.0 is user friendly & Intelligent software for homology or comparative modeling of protein three-dimensional structures. AutoMode 1.0 is based on JAVA, PYTHON 2.5. Integrated with Modeller v9.15.

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