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Keynote speakers
Picture of Davide Cacchiarelli
Picture of Martin Eisenacher
Picture of Artemis Hatzigeorgiou
Picture of Lennart Martens
Picture of Juan Antonio Vizcaino
Juan Antonio

Davide Cacchiarelli,
Telethon Institute of Genetics and Medicine, Naples, Italy.

Davide Cacchiarelli grew up in Rome where he carried out his undergraduate studies in Biotechnology and Biology. He obtained a Master Degree and a Doctorate Degree in Genetics and Molecular Biology from SAPIENZA – University of Rome, working on mechanisms of RNA regulation. In 2011 he moved to The Broad Institute of MIT and Harvard and The Department of Stem Cell and Regenerative Biology at Harvard University to focus his research on the rules governing cell fate transitions and reprogramming using genomic approaches.
He returned to Italy in 2017 thanks to the Armenise-Harvard Foundation Career Development Award and now he leads a young research group focused on understanding the dynamics of cell fate decisions at TIGEM, the Telethon Institute of Genetics and Medicine in Naples.
His work aims to identify the mechanisms controlling cell fate decisions during cellular differentiation, conversion and reprogramming, and how such processed are affected by genetic mutations of key regulatory proteins including transcription factors. To achieve this goal he proposes to integrate descriptive, functional and single cell genomics to dissect how genetic elements and their variants impinge on the temporal and spatial control of gene expression.

Integrative and single cell genomics approaches to dissect cell fate decisions and genetic disorders
A short abstract of the talk will be available here.

Martin Eisenacher,
Medizinisches Proteom-Center (MPC), Ruhr-Universität Bochum, Germany.

Martin Eisenacher is the leader of the “Medical Bioinformatics” department at the Medizinisches Proteom-Center, Ruhr-Universität Bochum, since 2015.
Since 2014, he is consortium speaker and project leader of several running projects funded by BMBF, Federal Ministry for Research and Innovation, Deutsche Gesetzliche Unfallversicheung (DGUV) and consortium speaker of the service center “Bioinformatics for Proteomics – BioInfra.Prot” within the BMBF funded “German Network for Bioinformatics Infrastructure – de.NBI”.
In 2014, he got his Habilitation (German qualification for higher education) in the medical faculty, at Ruhr-Universität Bochum, with a cumulative habilitation thesis on “Standard data formats, algorithms and analysis strategies for the bioinformatics of proteomics” and had his Habilitation colloquium at the faculty council on “Big data – chances and risks of personalised medicine“.
Since 2006, is has been project leader and coordinator of several finished projects funded by EU, BMBF, Federal Ministry for Research and Innovation, Deutsche Gesetzliche Unfallversicheung (DGUV), Cluster Industrielle Biotechnologie (CLIB), medical faculty RUB (FoRUM).

Bioinformatics tools and analyses in Proteomics
Proteomics, especially with mass spectrometry has reached many milestones. Several challenges postulated as being show stoppers have been addressed: identification with limited false positives, quantification, finding “all” gene-coded proteins, modifications (plus localization), usable standard formats. In parallel, instruments and algorithms became more sensitive, more exact and data more sustainable.
But there are still some unexplained phenomenons, all-day questions to solve, closed doors to open. For example, the increasing mass accuracy creates new challenges to false-discovery rate estimation. Or, shared peptides could be used for a better quantification.
To open the box of pandora – all our method development in mass spectrometry for Proteomics may become obsolete some day.

Artemis Hatzigeorgiou,
DIANA-Lab, Hellenic Pasteur Institute / Department of Computer & Communication Engineering, University of Thessaly, Greece.

Artemis Hatzigeorgiou is Principal Investigator at the B.S.R.C. “Alexander Fleming” and adjunct assistant Professor at the Department of Computer and Information Science at the University of Pennsylvania.
She received an MS in Computer Science from the University of Stuttgart and a PhD in Molecular Biology from the University of Jena in 2001. In the same year, she joined the University of Pennsylvania as assistant professor of bioinformatics with a joined appointment at the Department of Genetics, Medical School and the Department of Computer and Information Science at the Engineering School. In 2007, she joined as Principal Investigator the Institute of Molecular Oncology at the B.S.R.C. “Alexander Fleming” and she was elected adjunct professor at the Computer and Information Science department of the University of Pennsylvania.
Artemis Hatzigeorgiou received in 2003 the “Early Carrier Award” from the National Science Foundation of the USA.
She is co-author of the Stuttgart Neural Network Simulator (SNNS), a world-wide used open-source software for the simulation of Artificial Neural Networks. In 2003 she developed DIANA-microT, one of the first published microRNA target prediction programs. She has published in top tier journals as Nature, Science, PNAS, AJHG and G&D and has served as a panelist for NSF and the National Institute of Health of the USA. In 1996, she has been a co-founder of the computer science company Synaptic, Ltd, located at Herakleion, Crete.

Title to be defined
A short abstract of the talk will be available here.

Lennart Martens,
VIB, University of Gent, Belgium.

Title to be defined
A short abstract of the talk will be available here.

Juan Antonio Vizcaíno,
EMBL-European Bioinformatics Institute (EMBL-EBI)
Hinxton, Cambridge, United Kingdom.

Juan Antonio Vizcaíno is the Proteomics Team Leader at the EMBL-European Bioinformatics Institute (EMBL-EBI, Cambridge, UK). His team is responsible of the development of the PRIDE database, the world-leading public repository for mass spectrometry proteomics data (http://www.ebi.ac.uk/pride). In addition, he is coordinating the ProteomeXchange Consortium, aiming to standardize data submission and dissemination in proteomics resources worldwide. He has also heavily contributed to the development of proteomics data standard formats (mzIdentML, mzQuantML, mzTab, proBed, proBAM) and related software, and has participated in the development of several data deposition (e.g. PX submission tool) and visualization (PRIDE Inspector) stand-alone tools. Furthermore, he coordinated the development of the two iterations of the “PRIDE Cluster” spectral clustering algorithm and have participated in the maintenance and refinement of other widely-used bioinformatics services. He actively promotes open data policies in the proteomics field.
He has been the leading author of high impact publications in Nature Biotechnology, Nature Methods, Nucleic Acids Research, Genome Biology and Molecular and Cellular Proteomics, among other journals. Overall, he has published >110 articles with >9,700 citations (h-index=41, Google Scholar), largely in computational mass spectrometry and bioinformatics. Originally, he earned undergraduate degrees in Pharmacy and in Biochemistry, a Masters’ degree in Microbiology, and a doctoral degree in Molecular Biology from the University of Salamanca, Spain.

“Big data” approaches in proteomics: Re-use of public proteomics datasets
First of all, I will summarize the work we have done in the last years to create an infrastructure to enable data sharing of mass spectrometry (MS) proteomics data in the public domain, including the development of the world-leading PRIDE database (https://www.ebi.ac.uk/pride/), the related tools and software, open data standards and the establishment of the worldwide ProteomeXchange Consortium of proteomics resources (http://www.proteomexchange.org/).
Thanks, among other efforts, to the great success of PRIDE and ProteomeXchange, the proteomics community is now widely embracing open data policies, an opposite scenario to the situation just a few years ago.
To corroborate this, during 2018 approximately 300 datasets per month have been submitted to PRIDE, which is now approaching the PB scale. This plethora of public proteomics data is being increasingly reused by the research community, since there are indeed highly attractive applications for data scientists. Some of them are proteomics centric (e.g. meta-studies to expand the knowledge of the human proteome, generation of spectral libraries, etc…), but others involve the integration between proteomics and other omics data types, especially genomics.
In this context, I will outline a few projects that we are carrying out in-house, e.g. the generation of the functionally-relevant human phospho-proteome or the integrative analysis of protein expression in human cancer. I will explain at least one of them in higher detail.

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