Antonio Rosato

Antonio Rosato, born in 1971, received his PhD in Chemistry in 1998 at the University of Florence. He is Associate Professor at the University of Florence since 2002. Metalloproteins are the main focus of his research activities.

Antonio Rosato is actively working on the implementation of bioinformatic research on metalloproteins. Previously, he developed innovative methodologies for the study via NMR of the solution structure of paramagnetic metalloproteins. Another active area of research is the implementation of tools for NMR data analysis and molecular dynamics simulations using distributed computational infrastructures. The latter activities are carried out within various international collaborations funded also by the European Commission. Antonio Rosato co-authored about 100 articles in international scientific journals. He has contributed to the determination of the structure in solution of around thirty metalloproteins. His H-index is 36 (ISI) / 40 (Google Scholar).

When: Day 1, 14th November, Session 4: Research Data Management in practice #Part 1, 14:15 - 15:15

INSTRUCT - Integrated Structural Biology Infrastructure

Magnetic Resonance Center, University of Florence and Consorzio Interuniversitario di Risonanze Magnetiche di Metalloproteine (CIRMMP) – banci@cerm.unifi.it, rosato@cerm.unifi.it           

Abstract. Structural biology is a discipline within the life sciences, one that investigates the molecular basis of life by discovering and interpreting the shapes of macromolecules. Structural biology has a strong tradition of data sharing, expressed by the founding of the Protein Data Bank (PDB) in 1971.

Since those early days, changes in research goals and methods have led to changes in the requirements for IT infrastructure. A common data infrastructure is required, providing a simple user interface and simple programmatic access to scattered data. Along with this goes the development of workflows that facilitate the use and reuse of datasets from different facilities and techniques. Within this context, the use of cloud storage resources can be quite beneficial, to organize data from multiple sources as well as to facilitate data transfer to/from different centers and repositories.

Journals accept structural papers only if the structure has been shared in the PDB/EMDB. The PDB and EMDB preserve the refined structural model, and some of the reduced experimental data and sample data, gathered by data harvesting tools. However, the larger primary experimental data is not deposited, and other archives have arisen to cater for this need. PDB entries are often reused: in 2012 to 2014 there were 5913 papers citing one or more PDB entries. Instruct’s Data Management Policy for Centres says “Instruct intends to provide ways to discover data obtained at the Research Infrastructure, with links to data wherever it was originally  collected or processed, and wherever  it  is currently stored ”. In addition, there are numerous databases and online resources derived from the PDB to facilitate browsing, finding and exploring its entries.

Although a lot has been achieved in terms of providing and reusing structural data, there is still work to be done to provide full traceability of the experimental workflow to the final 3D structure. Some data is “orphaned” when the metadata is lost. As projects get more complicated, this issue becomes worse. This is largely a result of the responsibility for data curation being placed with the individual researcher. The automatic acquisition of metadata would greatly reduce this loss. Another obstacle is the burden of installing and using a wide range of software. To counter this, access to software tools via web-based interfaces provides an efficient approach that allows individual users in any lab worldwide to successfully adopt state-of-the-art tools.