About

Prof. Dr. MD Eduardo Gade Gusmao is a Brazilian bioinformatician, professor, and writer. This site hosts his lab notes, blog posts, creative experiments, and tools for computer science, biological science, and beyond.

As a computational biologist with a strong focus on the integration of machine/deep learning, probabilistic modeling, and high-dimensional multi-omics biological data to elucidate the molecular and chromatin-level mechanisms of aging. His primary research interest lies in the study of chromatin conformation and its role in gene regulation, with the goal of developing Chromatin Architecture Biomarkers (CABs) that can serve as predictive markers for aging and age-related diseases. This work bridges computational and experimental approaches to investigate the intricate relationships between chromatin structure, epigenetic regulation, and gene expression in both normal and pathological cellular states.

To this end, he aims to advance methods that leverage hypergraph-based and deep probabilistic learning techniques to capture and model the spatial organization of chromatin. His vision is to establish a novel class of CABs that integrate insights from multi-omics datasets, enabling precise biomarker identification for aging interventions and immuno-celular therapies. With a foundation in both computational biology and molecular biology, and a growing expertise in laboratory techniques, he is well-positioned to develop innovative frameworks that unify large-scale multi-omics data, chromatin architecture studies, and precision medicine approaches to advance the understanding of cellular aging and to foster translational applications in therapeutic and pharmacogenomics research.

You can view his brief CV below (all dates in decreasing order) and his full CV at: Download my CV (PDF) You can reach him at eduardo.gusmao@tum-sls.de.

Personal data

Full name in native language: Eduardo Gade Gusmão

DOB: 1990-12-02

Areas of Study/Research/Leisure Interest (current research in bold):

1. Biology/Medical-Related Fields:

    - **Chromatin Molecular Biology.**

    - **Computational Biology / Health Informatics / Translational Medicine.**

    - Regulatory and Epigenetic Control of Gene Regulation.

    - Multi-Omics Techniques with Single-Cell and Spatially Resolved Variants.

    - **Public Health and Populational Genomics.**

2. Computational Fields:

    - Artificial Intelligence > Machine Learning.

    - **Deep Learning: Classical, Attention-Based & Variational Approaches.**

    - Deep Learning: Graph & Hypergraph Neural Networks.

    - **Artificial Intelligence / Deep Learning: Self-Supervision, Transfer Learning and Meta-Learning.**

    - Algorithmic Information Theory > Kolmogorov-Complexity

3. Applied and Pure Mathematical Fields:

    - Probability Theory and Statistical Applicability.

    - Calculus, Numeric Analysis and Computational Representation.

    - **Category Theory.**

Languages:

- Portuguese (Native).

- English (Full Professional Proficiency).

- Spanish (Full Professional Proficiency).

- German (Intermediate Proficiency).

- Italian (Intermediate Proficiency).

- Finnish (Intermediate Proficiency).

- French (Intermediate Proficiency).

- Dutch (Basic Proficiency).

- Chinese - Mandarim (Basic Proficiency).

Current number of pages fully understood of James Joyce's Finnegans Wake: 77/628

Education

Career History

Academia

Industry

Selected Skills

Computational & Data Analysis Skills:

• Programming Languages: Python, UNIX Bash, AWK, R, C/C++, Java, MATLAB, SQL.

• Packages: Biopython, Pandas, NumPy, SciPy, TensorFlow, PyTorch, Samtools, Matplotlib, Seaborn, Bioconductor, DESeq2.

• Coding Strategy: Jupyter Notebooks, RMarkdown, Git, OpenBPS+SLURM+Lustre, Mamba, Nextflow, Singularity, AWS.

• File Types: AB, SR(A|R), FAST(A|Q), (S|B|CR)AM, (BIG)BED, (BIG)WIG, (V|B)CF, G(T|F)F, HIC/(M)COOL, H(DF)5.

Selected Research and Lab Techniques:

• Basic Techniques: (RT-)(q)PCR, Extraction & Purification, Digestion & Ligation, Gel Electrophoresis, Nanodrop.

• Intermediate Techniques: Western Blotting, IP, ChIP, EMSA, Cell Culture, Flow Cytometry, IVT, RNAi, Sanger.

• Advanced Techniques: Microarrays, CRISPR Screens, (Single-Cell) NGS, Nanopore Seq., MSMS, Cryo-EM, iPSCs, STORM.

Selected Additional Tools and Resources:

• General Tools: Microsoft Office, LaTeX, Trello, Slack, Zotero, Zoom, Google Meeting, LabArchives (Inventory).

• Bioinformatics Tools: BWA, Bowtie2, STAR, Cutadapt, Picard, SAMtools, GATK, FastQC, VCFtools, Cufflinks, Gprofiler.

• Databases/Browsers: GEO, NIH/NCBI/PUBMED, ENCODE, UCSC, IGV, UCSC, WashU.

Other Relevant Skills:

• Advanced Grant Proposal Writing Skills.

• Advanced Knowledge of Modern Pedagogy.

• Project Management Experience: Led large-scale genomic projects coordinating over 10 international institutions and managing sample collection, sample WGS, genotype and phenotype data analysis and storage teams’ efforts exceeding $1 billion USD.

• Currently writing two books on "Introduction to Multi-Omics" and "Aleatory Theory".