As a multidisciplinary bioinformatics specialist, I bring a unique blend of skills in computational biology, data science, and molecular research. My expertise spans genomics, spatial and single-cell transcriptomics, and multi-omics integration, with a strong foundation in both academic research and industry applications. I am proficient in programming, data visualization, and statistical modeling, enabling me to extract meaningful insights from complex biological datasets to drive discoveries in cancer, aging, and lung diseases.Β
Programming & Scripting π₯οΈβ¨οΈ:
Expert in R (tidyverse, Bioconductor), Python (pandas, scikit-learn, TensorFlow), Julia, Linux/Bash scripting, and SQL for data analysis, pipeline automation, and database management.
Bioinformatics Software & Tools π§¬π§:
Extensive experience with:
Seurat, Scanpy, Monocle, Cell Ranger for single-cell RNA-seq analysis.
Limma, DESeq2, EdgeR for differential expression analysis.
GATK, CNVkit, Manta for variant calling and copy number variation analysis.
ANNOVAR, VEP for variant annotation.
CellPhoneDB, NicheNet, MultiNicheNetR, Giotto for cell-cell interaction and spatial transcriptomics analysis.
Nextflow, Snakemake for building and managing scalable, reproducible bioinformatics workflows.
Multi-Omics Data Integration & Mining ππ§¬:
Skilled at integrating genomics, transcriptomics, epigenomics, proteomics, and metabolomics datasets. Advanced data mining techniques for pattern recognition and biological insight extraction.
Single-Cell & Spatial Omics π§«π:
Expertise in scRNA-seq, scATAC-seq, CITE-seq, spatial transcriptomics (10x Visium, Xenium, NanoString GeoMx). Expert in cell type annotation, clustering, trajectory inference, and pathway analysis.
Biological Insight & Translational Analysis π§ π¬:
Strong understanding of biology to extract meaningful and translational insights from computational analyses, bridging data with clinical and experimental relevance.
Machine Learning & Predictive Modeling π€π:
Experience developing models for classification, clustering, and regression using scikit-learn, XGBoost, TensorFlow/Keras.
Cloud Computing & HPC βοΈβ‘:
Proficient in AWS, Google Cloud Platform, Slurm HPC clusters. Experience with Docker and Singularity containers for reproducible environments.
Laboratory Techniques π¬π§ͺ:
Practical experience in nucleic acid extraction, PCR, electrophoresis, and cell culture.
Graphic Design & Visualization π¨ποΈ:
Skilled in scientific figure and presentation design using Adobe Photoshop, Illustrator, and InDesign.
Leadership π§ββοΈπ₯:
Experience leading bioinformatics projects, coordinating interdisciplinary teams, and mentoring junior researchers and students.
Teamwork & Collaboration π€π€:
Proven ability to work effectively in diverse teams, fostering communication and collaboration across experimental and computational groups.
Teaching & Mentoring ππ¨βπ«:
Experienced in teaching bioinformatics concepts and tools to students and colleagues, organizing workshops, and providing ongoing support.
Project Management & Organization π
ποΈ:
Skilled in organizing complex projects, managing timelines and resources, and ensuring reproducible and well-documented workflows.
Communication π£οΈβοΈ:
Strong written and verbal communication skills, including scientific writing, presentations, and teaching bioinformatics topics.
Problem-Solving & Adaptability π§π§ :
Able to troubleshoot complex computational problems and adapt quickly to new technologies and evolving research needs.
Time Management & Multitasking β°π:
Efficient in managing multiple projects simultaneously, meeting deadlines, and organizing data and workflows for reproducible research.