From sequence processing to pipeline development, I have extensive experience in omics data analysis using a broad range of bioinformatics tools. I’m proficient in Python and R for data analysis and routinely work in Linux environments, ensuring efficiency, reproducibility, and scalability across projects.

My expertise lies in statistical modeling and data visualization, enabling me to extract meaningful insights from complex datasets. From inferential statistics to multivariate analyses, I also have hands-on experience applying machine learning techniques to explore and interpret biological data.

With a strong background in biology, I’ve developed a deep understanding of genomics, spanning areas such as gut microbiota and bacterial genetics. I’m able to lead projects from conception to completion, whether that means publishing research findings or delivering comprehensive analytical reports.

A comprehensive analysis of the progression of a MRSA clone, which emerged during an outbreak, was conducted utilizing machine learning and next-generation sequencing technologies over the course of a decade.

Comprehensive studies of DIP-STR markers in human DNA have facilitated the identification of the lesser contributor in highly imbalanced blood mixtures, such as those found at crime scenes or during pregnancy testing.

Creation of a web-based tool designed to streamline the generation of patient tracking charts and networks for infection control personnel, thereby enhancing surveillance speed and overall infection management within the hospital setting.

Offshore drilling platforms can cause harm to nearby marine life through spills, leaks, or drilling operations. We assessed the environmental impact using sediment samples and next-gen sequencing techniques to derive ecological status indices.

Understanding antibiotic resistance spread requires tracking plasmids, which are key transmitters. We employed long-read whole-genome sequencing on carbapenemase-resistant isolates to decode plasmid transmission dynamics in multiple hospital outbreaks.

The use of mNGS for infection diagnosis is rising due to its ability to rapidly detect pathogens. We investigated the influence of bacterial DNA enrichment on mNGS-based detection and estimation of bacterial abundance in an infected tissue model.

Foraminifera, a group of eukaryotic protists, have a complex phylogeny partly due to limited genomic data. In an effort to address this, we conducted an analysis of transcriptomic data from 28 species to construct the most comprehensive phylogeny to date.

Correctly identifying the serotypes of infectious Streptococcus pneumoniae strains is vital for effective vaccine development. We assessed the efficacy of molecular-based methods (including WGS) compared to the traditional biochemical approach.

The emergence of azithromycin resistance poses significant challenges in treating numerous bacterial infections. Our study delved into the effects of genetic mutations on the azithromycin resistance levels exhibited by different strains of Nesseria gonorrhoeae.

Bioinformatics has become increasingly essential in modern biology, every biologist now benefits from having at least a basic understanding of computational tools. However, finding the right learning resources can often be time-consuming and overwhelming.


To help beginners get started, I’ve compiled a collection of useful resources that I’ve personally found valuable. These are not tutorials, but rather pointers to help you identify what to learn and where to start. There are many excellent tutorials available online, and I aim to update this list regularly to keep it relevant and helpful.