Sergio Castillo

Sergio Castillo

Software Developer

Biography

Software developer with experience in both academia and industry. During my PhD I worked in uncovering the mechanisms of regeneration of the planaria Schmidtea mediterranea, by integrating transcriptomic datasets with gene-protein networks into web applications, making use of machine learning and several statistical approaches. I fell in love with software development, and that’s what I do now.

Interests

  • Back end development
  • Databases
  • Machine Learning
  • Data Visualization

Education

  • PhD in Genetics, Current

    Universitat de Barcelona

  • M.Sc. Bioinformatics for Health Sciences, 2017

    Universitat Pompeu Fabra

  • B.Sc. Biology, 2015

    Universitat de Barcelona

Skills

Python

django

Django

R

perl

Perl

Docker

Machine Learning

Experience

 
 
 
 
 

Software Developer

Elements Interactive

Apr 2020 – Present Barcelona
  • Developed RESTful APIs using Python/Django.
  • Made use of Docker, Kubernetes, and CI/CD for deploying and scaling applications.
 
 
 
 
 

PhD Fellow

Computational Genomics Lab, University of Barcelona

Apr 2017 – Apr 2020 Barcelona
  • Developed bioinformatics software, machine learning pipelines, and other research tools.
  • Analyzed large sequence datasets: RNA-seq, single-cell RNA-seq, ChIP-seq, ATAC-seq.
 
 
 
 
 

Research Intern

Computational Genomics Lab, University of Barcelona

Apr 2017 – Apr 2020 Barcelona
  • Analyzed protein-protein graph/network related to retinitis pigmentosa disease.
  • Implemented a text mining pipeline to extract interactions from articles.

Recent Publications

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PlanExp: intuitive integration of complex RNA-seq datasets with planarian omics resources

In this work, we present PlanExp, a web-application to explore and visualize gene expression data from different RNA-seq experiments (both traditional and single-cell RNA-seq) for the planaria Schmidtea mediterranea. PlanExp provides tools for creating different interactive plots, such as heatmaps, scatterplots, etc. and links them with the current sequence annotations both at the genome and the transcript level thanks to its integration with the PlanNET web application.

PPaxe: easy extraction of protein occurrence and interactions from the scientific literature

We have developed PPaxe, a python module and a web application that allows users to extract PPIs and protein occurrence from a given set of PubMed and PubMedCentral articles. It presents the results of the analysis in different ways to help researchers export, filter and analyze the results easily.

RPGeNet v2.0: expanding the universe of retinal disease gene interactions network

RPGeNet integrates interaction information from STRING, BioGRID and PPaxe, along with retina-specific expression data and associated genetic variants, over a Cytoscape.js web interface. For the new version, RPGeNet v2.0, the database engine was migrated to Neo4j graph database manager, which speeds up the initial queries and can handle whole interactome data for new ways to query the network. Further, user facilities have been introduced as the capability of saving and restoring a researcher customized network layout or as novel features to facilitate navigation and data projection on the network explorer interface. Responsiveness has been further improved by transferring some functionality to the client side.

PlanNET: homology-based predicted interactome for multiple planarian transcriptomes

We have developed a protocol to predict protein–protein interactions using sequence homology data and a reference Human interactome. This methodology was applied on 11 Schmidtea mediterranea transcriptomic sequence datasets. Then, using Neo4j as our database manager, we developed PlanNET, a web application to explore the multiplicity of networks and the associated sequence annotations.