About me

I love bioinformatics and the challenge of dissecting biological data, especially regarding Systems Biology and Deep Learning. Currently, I am the bioinformatician of the Bas van Steensel lab, where we develop new technologies to understand gene regulation better. In this context, I'm mainly responsible for developing computational tools that follow these technologies.

Interests: Bioinformatics; Computational Biology; Deep Learning; Systems Biology; Evolution

Main computational tools

PARM: Promoter Activity Regulatory Model

Deep Learning Gene Regulation Python

PARM is a deep learning model that predicts the promoter activity from the DNA sequence itself. We trained PARM on a specific type of MPRA data that allows it to predict cell-specific promoter activity in a lightweigth and fast manner. In addition to developing PARM together with my colleagues, I was also responsible for publishing it as a Bioconda package and maintaining the codebase.

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Domainogram

Gene Regulation R

Domainogram is a type of plot that shows differences in nuclear lamina interactions between two conditions using pA-DamID data. I've done a rework in the original code. My version is based on ggplot2 to make it more flexible and easier to use. Also, I've coded some additional functions to generate the domainograms when the conditions are recombinations (e.g. deletions or insertions).

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CURE: automated and parallel pipeline for the Curation of UltraconseRved Elements (UCEs)

Phylogenomics Python Bash

CURE is a framework to curate UCE data for species-tree reconstruction. When dealing with UCE data, there are two main ways to cure the data (more info in our paper). None of them was automated or efficiently suitable for large datasets. Guided by my colleagues, I developed CURE to solve this problem. CURE is user-friendly and speeds up the curation process by parallelizing the steps.

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Publications

Research papers

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1. Barbadilla-Martínez, L.; Klaassen, N.*; Franceschini-Santos, V. H.*; Breda, J.; Hernandez-Quiles, M.; van Lieshout, T.; Urzua Traslaviña, C.; Yücel, H.; Boi, M.; Hermana-Garcia-Agullo, C.; Gregoricchio, S.; Zwart, W.; Voest, E.; Franke, L.; Vermeulen, M.; de Ridder, J., van Steensel, B. (2024). The regulatory grammar of human promoters uncovered by MPRA-trained deep learning. BioRxiv.
   _{* Equal contribution}


2. Dauban, L., Eder, M., de Haas, M., Franceschini-Santos, V. H., Yañez-Cuna, J.O., van Schaik, T., Leemans, C., Rademaker, K., Martinez-Ara, M., Martinovic, M., de Wit, E., van Steensel, B. (2023); Genome-nuclear lamina interactions are multivalent and cooperative. BioRxiv


3. Manjón, A. G., Manzo, S. G., Prekovic, S., Potgeter, L., van Schaik, T., Liu, N. Q., Flach, K., Peric-Hupkes, D., Joosten, S., Teunissen, H., Friskes, A., Ilic, M., Hintzen, D., Franceschini-Santos, V. H., Zwart, W., de Wit, E., van Steensel, B., & Medema, R. H. (2023). Perturbations in 3D genome organization can promote acquired drug resistance. Cell reports, 42(10), 113124. Advance online publication.


4. Freitas, F.V.; Branstetter, M.G.; Franceschini-Santos, V. H.; Dorchin, A.; Wright, K.; Lopez-Uribe, M.; Griswold, T.; Silveira, F.A.; Almeida, E.A.B. UCE phylogenomics, biogeography, and classification of long-horned bees (Hymenoptera: Apidae: Eucerini), with insights on using specimens with extremely degraded DNA. Insect Systematics and Diversity, Volume 7, Issue 4, July 2023, 3


5. Pessoa-Lima, C.; Tostes-Figueiredo, J.; Macedo-Ribeiro, N.; Hsiou, A.S.; Muniz, F.P.; Maulin, J.A.; Franceschini-Santos, V. H.; de Sousa, F. B.; Barbosa, F., Jr.; Line, S.R.P.; et al. Structure and Chemical Composition of ca. 10-Million-Year-Old (Late Miocene of Western Amazon) and Present-Day Teeth of Related Species. Biology 2022, 11, 1636