Muhammad Asif (CENTURI Multi-engineering platform)

Bioinformatics Data Analyst


March 2019 - Present | Data analyst – bioinformatics (Research engineer), CENTURI Multi-engineering Platform, Aix-Marseille University (Marseille, France)

February 2020- August 2020 | Senior Bioinformatician and Data manager at iBET - Instituto de Biologia Experimental e Tecnológica Oeiras, Portugal

January 2019 – January 2020 | Bioinformatics Project Leader at SGS Molecular, Lisbon Portugal

July 2018 – December 2018 | Research Associate at LASIGE, Faculty Of Sciences, University Of Lisbon Portugal

March 2014 – October 2018 | PhD Researcher at BioISI, Faculty Of Sciences, University Of Lisbon Portugal

July 2013 – February 2014 | Bioinformatics Lecturer at COMSATS University Islamabad, Pakistan

2011 – 2013 | M.Phil in Bioinformatics from National Center of Bioinformatiocs, Quaid-i-Azam University Islamabad, Pakistan

2006 – 2010 | BS (Hons) in Bioinformatics from GCUF, Faisalaabd Pakistan

I am a Bioinformatician and data analyst with experience from both, academia and industry. I am proficient in developing data management infrastructure, providing bioinformatics research data analysis solutions and training, coupled with assisting postdocs and principal investigators in writing research proposal of bioinformatics data science.

I started bioinformatics in 2006 with a 4 year BS degree in bioinformatics that was followed by master’s in bioinformatics. My PhD in systems biology was focused on OMICS data integration and the development of integrative and predictive approaches for integrated data-sets.

Previously in industry, I was providing bioinformatics support that range from a simple database or tool selection to complete data analysis pipeline development (NGS, bulk RNA seq, single-cell RNA, functional enrichment analysis, 16s and metagenomics). Besides this, I am also proficient in developing highly sophisticated and customized solutions based on data integration, machine/deep learning and NLP methods.

The strong bioinformatics background enabled me to apply different concepts from Artificial Intelligence (AI), Network Biology, Systems Biology, and Natural Language Processing (NLP) to propose integrative, explorative and predictive approaches for biological data analysis.

Keywords : Bioinformatics, Systems Biology, machine learning, Network Biology, 16s analysis, bulk or single-cell RNA seq, text mining, and node/graph embedding.