Dr Marta Milo

Dr Marta MiloLecturer in Computational Biology
Department of Biomedical Science
The University of Sheffield
Western Bank
Sheffield S10 2TN
United Kingdom

Room: Alfred Denny C224a
Telephone: +44 (0) 114 222 4673
Email : m.milo@sheffield.ac.uk


General

Career history

  • 2012-present: Lecturer in Computational Biology
  • 2008-2012: Bioinformatics Research Fellow, NIHR Cardiovascular Biomedical Research Unit, Sheffield Teaching Hospitals NHS Trust.
  • 2004-2008: Wellcome Trust Research Fellow, University of Sheffield, UK.
  • 2003-2004: Postdoctoral Researcher at the Department of Biomedical Science, University of Sheffield, UK.
  • 2001-2003: Postdoctoral Fellow at the Dept of Computer Science, University of Sheffield, UK.
  • 1996-2000: PhD in Applied Mathematics and Computer Science at the University of Naples 'Federico II'.
  • 1995-1996: Computer Science and Statistics Consulting at FORMEZ c/o OLIVETTI Research Centre, Arco Felice, Italy.
  • 1994-1995: Qualification in Computer Science and Statistics applied to Public Administrative systems, at FORMEZ c/o OLIVETTI Research Centre, Arco Felice, Italy..
  • 1989-1994: Degree in Mathematics, University of Naples "Federico II'', Italy.

Education

  • 2000: PhD in Applied Mathematics and Computer Science, The University of Naples, "Federico II"
  • 1994: "Laurea" in Mathematics, The University of Naples "Federico II"

Research interests

To understand and define the source of uncertainty in quantitative biology it is a key aspect for improving sensitivity and accuracy in the analysis of high throughput genomic data. My research interests focus on developing computational tools, pipelines, appropriate experimental designs and protocols to assist in improving accuracy and sensitivity in the analysis of biological data. Major research activities are:

  • propagation of uncertainty, associated to low-level data, in downstream analysis of microarray data;
  • quantification and inference of gene expression levels using probabilistic models;
  • inference of gene networks using regulatory data and gene expression data;
  • Integrated approaches for the analysis of Next Generation Sequencing data.

My research group is part of the Centre for Stem Cell Biology (CSCB)

CSCB

Activities and distinctions

  • Member of  PUMA project (Propagating Uncertainty in Microarray Analysis)
  • Reviewer for leading scientific journals
  • Member of Quantitave Biology Group
  • Fellow of the Higher Education Academy, FHEA (as part of the University Postgraduate Certificate in Learning and Teaching)

Awards

  • Wellcome Trust Advanced Training Fellow (2004-2008)
  • Bioinformatics Research Fellow
  • NIHR Cardiovascular Biomedical Research Unit (2009-2012)

Funding

  • Wellcome Trust
  • British Heart Foundation
  • Royal Society
  • HEFCE

Recent publications

Full publications

Research Overview

Computational Biology

The main aim in my professional career has been to develop truly interdisciplinary skills, complementing and refining my bioinformatics skills with a deep understanding of the biological and experimental nature of the data collected. This is to better identify limitations in the experimental designs and better quantify variations in the data collection and validation. My work, so far, has been concentrating on the analysis and interpretation of high-throughput biological data, with the aim to produce feasible and robust hypothesis for a deeper understanding of the biological systems under study.

My research mainly focuses on developing computational tools that are assisting in improving accuracy of both low-level and downstream analysis of biological data. In collaboration with PUMA (Propagating Uncertainty in Microarray Analysis) group we have developed a family of probabilistic models, that estimate gene expression levels with credibility intervals to quantify the measurement variance associated with the estimates of target concentration within a sample. This Project was developed into a software package: puma, that is fully integrated in Bioconductor – Open Source Software for Bioinformatics.

I am currently working to extend the use of probabilistic models to Next Generation Sequencing data. This is done in close collaboration with the PUMA project to extend it to Next Generation Sequencing (NGS) data applications and with the newly formed Sheffield Bioinformatics Hub.

My main research interests are:

  • Genetic profiling of mammalian ear
  • Trascriptomic changes in stem cell in  3D culture.
  • Data integration methods  for large data

Figure 1