Skills

R

100%

python

90%

Statistics

80%

Visualization

70%

Neurodegeneration

80%

Experience

 
 
 
 
 
April 2019 – Present
Cambridge

Research Scientist - Bioinformatics Core Supervisor

Picower for Memory and Learning Institute - MIT

Responsibilities include:

  • Leading miRNA transcriptomic open project
  • Analysing genomic/transcriptomic data
  • Developing bioinformatic tools
  • Infrastructure architect
  • Managing knowledge-base platform
  • Teaching development
  • Mentoring
 
 
 
 
 
June 2017 – April 2019
Boston

Research Scientist

Harvard Chan School

Responsibilities include:

  • Leading miRNA transcriptomic open project
  • Analysing genomic data
  • Developing bioinformatic tools
  • Managing knowledge-base platform
  • Mentoring
 
 
 
 
 
May 2014 – June 2017
Boston

Research Associate

Harvard Chan School

Analyzed sequencing data in pathogenic conditions. Developed bioinformatics tools for sequencing data (RNA-seq, smallRNA-seq, ChIP-seq, ATAC-seq).
 
 
 
 
 
February 2013 – April 2014
Barcelona

Post-doctoral fellow

Institute of Biotechnology and Biomedicine

Detected de-novo transcripts as effect of inversion in the HapMap population.Expression quantitive trait loci analysis of inversion in the HapMap population.
 
 
 
 
 
September 2011 – February 2013
Barcelona

Post-doctoral fellow

Institute of Predictive and Personalized Medicine of Cancer

Determined small RNA characterization in human sperm samples.

Selected Publications

Background: MicroRNAs (miRNAs) are small RNA molecules (̃22 nucleotide long) involved in post-transcriptional gene regulation. Advances in high-throughput sequencing technologies led to the discovery of isomiRs, which are miRNA sequence variants. While many miRNA-seq analysis tools exist, a lack of consensus on miRNA/isomiR analyses exists, and the resulting diversity of output formats hinders accurate comparisons between tools and precludes data sharing and the development of common downstream analysis methods. Findings: To overcome this situation, we present here a community-based project, miRTOP (miRNA Transcriptomic Open Project) working towards the optimization of miRNA analyses. The aim of miRTOP is to promote the development of downstream analysis tools that are compatible with any existing detection and quantification tool. Based on the existing GFF3 format, we first created a new standard format, mirGFF3, for the output of miRNA/isomiR detection and quantification results from small RNA-seq data. Additionally, we developed a command line Python tool, mirtop, to manage the mirGFF3 format. Currently, mirtop can convert into mirGFF3 the outputs of commonly used pipelines, such as seqbuster, miRge2.0, isomiR-SEA, sRNAbench, and Prost!, as well as BAM files. Its open architecture enables any tool or pipeline to output results in mirGFF3. Conclusions: Collectively a comprehensive isomiR categorization system, along with the accompanying mirGFF3 and mirtop API provide a complete solution for the standardization of miRNA and isomiR analysis, enabling data sharing, reporting, comparative analyses, and benchmarking, while promoting the development of common miRNA methods focusing on downstream steps to miRNA detection, annotation, and quantification.
bioRxiv, 2018

Recent Publications

More Publications

Background: MicroRNAs (miRNAs) are small RNA molecules (̃22 nucleotide long) involved in post-transcriptional gene regulation. Advances …

Circulating small RNAs, including miRNAs but also isomiRs and other RNA species, have the potential to be used as non-invasive …

Recent & Upcoming Talks

High percentage of miRNA variants (isomiRs) may be sequencing artifacts.

Study of miRNA variants (isomiRs) accuracy by sequencing technologies.

MicroRNAs (miRNAs) are small RNA molecules (~22 nucleotide long) involved in post-transcriptional gene regulation. Advances in …

The study of small RNA helps us understand some of the complexity of gene regulation of a cell. Of the different types of small RNAs, …

Recent Posts

More Posts

We use bcbio-nextgen for the analysis of sequencing data, mainly, (sc)RNAseq, smallRNAseq, DNASeq and ChIPSeq. It is not rare that we …

This post will show how to configure quickly the colors for the annotation of rows/columns that go on top or on the side of a heatmap. …

Teaching

  • Small RNAseq analysis, Harvard T.H. Chan School of Public Health, Boston, MA 2015-2018
  • Data visualization, PRBB, Spain 2013
  • Workshop of ChIP-Seq analysis, University of Vic, Spain 2013
  • Workshop of Metagenomic, University of Vic, Spain 2013
  • Workshop of small RNA analysis, CRG, Spain 2010

Contact

  • Building 2 Room 202, Harvard Chan School of Public Health, Boston, 02115, USA