IX Proteomics Workshop

Click here to access the Abstracts List

Click here to access the list of selected applicants for the IX Proteomics Workshop.

The IX Proteomics Workshop is promoted by the Brazilian Biosciences National Laboratory (LNBio). The event will be hosted by the Brazilian Center for Research in Energy and Materials (CNPEM) in Campinas-SP, Brazil, on November 12^th and 13^th, 2019. The meeting program comprises classes ministered by experts and poster sessions.

IX Proteomics Workshop will offer 2-day courses in advanced themes in Omics Data Analysis. The lecturers will be ministered by 3 Brazilians and 4 foreign invited scientists. This edition will cover Data Integration, Computational and Statistical methods applied for Omics. The topics will be addressed in one-hour theoretical lecture and one-hour practical activity for each speaker.

Why participate?

This meeting represents a training opportunity for current and future users of proteomics and mass spectrometry. Following the example of the previous editions, held in the last eight years, the workshop also promotes the interaction between Brazilian and international researchers and dissemination of knowledge in the scientific community.

How much will I invest?

The IX Proteomics Workshop registration fee is mandatory for all participants. The registration fee includes all lectures, conference material, coffee breaks, cocktails and lunches at the event on November 12^th and 13^th  2019.

Details about the registration and the payment procedures are available in “Applications“.

IX Proteomics Workshop Deadlines
Applications	From September 26th to October 6th
Releasing of shortlisted applicants	October 23th
Waiting list call	October 30th
Workshop	From 12th to 13th of November

 

Speakers

Daniel Clarke, Icahn School of Medicine at Mount Sinai, New York
http://labs.icahn.mssm.edu/maayanlab/team/

Title: Integrating Bioinformatics Tools for Knowledge Exploration Workflows

To form novel hypotheses biomedical researchers rely more and more on information stored in public databases and bioinformatics tools that can query these databases. We have integrated several widely used bioinformatics tools and databases developed by the Ma’ayan Laboratory into a directed multi-graph with nodes representing fundamental data objects, for example, gene sets, signatures, disease or drug terms, and edges representing the transformations performed by various tools (for example, enrichment analysis, principal component analysis, or a PubMed search). We then use this graph to direct and facilitate user-driven exploration of the landscape of available knowledge stemming from an initial query or from a given dataset. As a case study, we use this system to investigate the role of under-studied protein kinases in diabetic nephropathy.

Dexter Pratt, UC San Diego School of Medicine, San Diego
https://home.ndexbio.org/team-members/

Title: Investigation of Proteomic Datasets using Biological Network Analysis Tools in the Cytoscape Ecosystem

Analyses based on molecular interaction networks and pathway mechanism models have a long history of use in the investigation of high throughput gene expression and proteomic data. The widely used Cytoscape desktop application (cytoscape.org) is one of preeminent tools in this field and is evolving into an ecosystem of both desktop, cloud services and web applications. NDEx, the Network Data Exchange (ndexbio.org), is a central element of the Cytoscape cloud that is a resource for network content and a framework for storing, sharing, publishing and computing with networks. This presentation will review Cytoscape tools relevant to the analysis of proteomic datasets including NDEx, Cytoscape desktop apps, and new web applications. In the following workshop, participants will apply tools described in the presentation to the investigation of an example data set.

Igor Jurisica, University Health Network, Toronto, Ontario
https://www.uhnresearch.ca/researcher/igor-jurisica

Title: Data-driven (precision) medicine: from data to models to insights and treatments

To fathom complex disease development processes, we need to systematically
integrate diverse types of information and link them using relevant
annotations and relationships, leading to meaningful modeling. This ranges
from multiple high-throughput datasets, functional annotations and
orthology data to expert knowledge about biochemical reactions and
biological pathways. Such integrative systems are used to develop new
hypotheses and answer complex questions such as what type of system
perturbation may result in a desired change in cellular function; what
factors cause disease; will patients respond to a given treatment, etc.

Precision medicine needs to be data-driven and corresponding analyses
comprehensive and systematic. We will not find new treatments if only
testing known targets and studying characterized pathways. Thousands of
potentially important proteins remain pathway or interactome “orphans”.
Computational biology methods can help fill this gap with accurate
predictions, but the biological validation and further experiments are
essential. Intertwining computational prediction and modeling with
biological experiments will lead to more useful findings faster and more
economically.

These computational predictions improved human interactome coverage
relevant to both basic and translational research, and importantly, helped
us to identify, validate and characterize prognostic signatures. Combined,
these results may lead to unraveling mechanism of action for therapeutics,
re-positioning existing drugs for novel use and prioritizing multiple
candidates based on predicted toxicity, identifying groups of patients
that may benefit from treatment and those where a given drug would be
ineffective.

Application of graph theory, data mining, machine learning and advanced
visualization enables data-driven, precision medicine. Intertwining
computational prediction and modeling with biological experiments will
lead to more useful findings faster and more economically.

João Carlos Setubal, Chemistry

Institute, University of São Paulo, SP
http://www.iq.usp.br/setubal/

Title: A transcriptome-based signature of pathological angiogenesis predicts breast cancer patient survival

Compostagem termofílica é uma rica fonte de enzimas relacionadas com degradação de biomassa. No projeto metazoo estudamos a compostagem realizada no Parque Zoológico de São Paulo utilizando sequenciamento de nova geração. Com base no sequenciamento do DNA total (shotgun) de dezenas de amostras, montamos um catálogo com mais de 10 milhões de sequências codificadoras de proteínas.  Esse catálogo foi mineirado em busca de enzimas termoestáveis com bom potencial tecnológico. Através de uma metodologia de aprendizado de máquina chegamos a um subconjunto de 231 enzimas candidatas promissoras. Para quatro dessas candidatas realizamos ensaios experimentais confirmando termoestabilidade e atividade enzimática.

Lydia Y. Liu, University of Toronto
http://kislingerlab.uhnres.utoronto.ca/people.html

Title: Proteomics Data Integration in Cancer: The Value of Multimodality

“Increasingly translational cancer studies will quantify many types of molecular information in specific model systems or patient samples. These most frequently include the germline and somatic mutation profiles (including point mutations, copy number aberrations and genomic rearrangements), the transcriptome, immune infiltrates, the epigenome and the evolutionary timing of variants at each of these levels. Proteomic data analyses thus need to leverage that data to better understand information flow in cancer cells, develop robust biomarkers and understand the molecular origins of complex phenotypes. We will discuss the broad data-analytic strategies for these large datasets, and the challenges with integrating proteomic data with other datatypes. This will include practical examples of recent work performing such integrative analyses in primary cancer cohorts, and the value of statistical, machine-learning, information-theoretic and network strategies. Overall, we show that data integration across multiple levels of the central dogma improves our understanding of cancer phenotypes. Indeed biomarkers comprising multiple classes of biomolecules systematically outperform those that include only one: despite being an analytic challenge, multi-modality is a key opportunity for the future development of oncoproteomics.”

Mariana Boroni, National Cancer Institute, RJ
https://www.inca.gov.br/en/node/2375

Title: Identifying new therapeutic strategies for Colorectal cancer in the Big Data Era.

O câncer colorretal (CCR) é um dos carcinomas de maior incidência e mortalidade no mundo e tem como fatores de risco o baixo consumo de vegetais e alto consumo de carne vermelha e/ou processada, sobrepeso e sedentarismo. O CCR é uma doença altamente heterogênea, apresentando quatro subtipos moleculares, com diferenças na localização anatômica, no microambiente tumoral e nas vias moleculares alteradas. Essa grande heterogeneidade afeta significativamente a resposta a diferentes tratamentos e o prognóstico dos pacientes. Neste sentido, novas estratégias terapêuticas devem ser desenvolvidas considerando-se as alterações moleculares mais relevantes nos subtipos moleculares tumorais. As análises para identificação de alvos terapêuticos se baseiam no conceito de “druggable genome”, isto é, identificação de genes que codificam famílias protéicas específicas que interagem com fármacos, e que estão diretamente relacionados com o estabelecimento da doença. Com base nestas informações, o objetivo do nosso estudo é sugerir o reposicionamento de drogas atualmente utilizadas para o tratamento de outros tipos tumorais, assim como a identificação de novos alvos terapêuticos a partir da análise dos padrões de expressão gênica e do perfil de interação proteína-proteína nos subtipos moleculares de CCR.

Nina Hirata, Institute of Mathematics and Statistics, University of São Paulo, SP
https://www.ime.usp.br/~nina/

Title: Machine Learning and Computational Thinking

Machine learning techniques are tools often used to automate certain
types of data processing needed for data analysis. They are
particularly useful to analyze multidimensional data of complex nature
or large amounts of data. In this talk we will start relating
computational algorithms to machine learning and discussing how
computational thinking is essential for the effective use of
computational tools, including machine learning techniques. We will
then introduce basic concepts and methods of machine learning.
At the end, the discussed concepts and methods will be explored
through practical hands-on application examples.

 

Program

November 12th, 2019
8:00-9:00	Reception and Registration
9:00-9:30	Welcome – Kleber Franchini and Adriana Paes Leme,
9:30-10:30	Lydia Y. Liu, University of Toronto Proteomics Data Integration in Cancer: The Value of Multimodality
10:30-10:40	Viviane Nascimento, Waters
10:40-11:40	Lydia Y. Liu, Hands-on
11:40-12:10	Coffee break and Poster session
12:10-1:10	Dexter Pratt, UC San Diego School of Medicine, San Diego Investigation of Proteomic Datasets using Biological Network Analysis Tools in the Cytoscape Ecosystem
1:10-2:30	Lunch
2:30-3:30	Dexter Pratt, Hands-on
3:30-3:40	Felipe Lugão, NovaAnalítica/Thermo Scientific
3:40-4:40	Nina Hirata, Institute of Mathematics and Statistics, University of São Paulo, SP Machine Learning and Computational Thinking
4:40-5:10	Coffee break and Poster session
5:10-6:10	Nina Hirata, Hands-on
6:10-6:30	Discussion
6:30-8:30	Welcome Reception
November 13th, 2019
8:00-9:00	João Carlos Setubal, Chemistry Institute, University of São Paulo, SP Mining of thermostable enzymes from compost metagenomic data
9:00-9:10	Diego Assis, Bruker timsTOF fleX with ESI and MALDI for Proteomics and SpatialOMx
9:10-10:10	João Carlos Setubal, Hands-on
10:10-10:40	Coffee break and Poster session
10:40-11:40	Mariana Boroni, National Cancer Institute, RJ Identifying new therapeutic strategies for Colorectal cancer in the Big Data Era
11:40-12:40	Mariana Boroni, Hands-on
1:00-2:00	Lunch
2:00-3:00	Daniel Clarke, Icahn School of Medicine at Mount Sinai, New York Integrating Bioinformatics Tools for Knowledge Exploration Workflows
3:10-3:20	Maurício Marques, Agilent
3:20-4:20	Daniel Clarke, Hands-on
4:20-4:50	Coffee break and Poster session
4:50-5:50	Igor Jurisica, University Health Network, Toronto, Ontario Data-driven (precision) medicine: from data to models to insights and treatments
5:50-6:50	Igor Jurisica, Hands-on
6:50-7:00	Final Remarks

          

List of selected applicants

Click here to access the Abstracts List

The application form is available until October 6th.

Please, read all the information below carefully before filling the form.

How to apply

• All the applicants must submit an abstract to present their research during the poster sessions;
• The registration period is from September 26th to October 6th. 

Selection of applicants

Attendance is limited to 50 places and application is required;

Candidates will be selected based on the following criteria.

1. Complete Postdoctoral’s Degree;
2. Incomplete Postdoctoral’s Degree;
3. Complete Doctoral’s Degree;
4. Incomplete Doctoral’s Degree;
5. User of Mass Spectrometry Laboratory (LNBio);
6. Number of published or accepted manuscripts;
7. Complete/Incomplete Masters’ or Bachelor’s Degree
8. Experience in the field.

Confirmation and payment

• All the selected applicants will receive an e-mail with the payment procedure;
• The IX Proteomics Workshop registration fee is mandatory for all selected participants. Please, see the ratings below.

Undergraduate students; Technicians, Masters, PhD….….…..R$ 200,00

Post-doc in progress, post-doc degree and professionals……R$ 300,00

• The registration will be from September 26^thto October 6^th. The registration will only be concluded after the fee payment according to your category.

All selected participants will receive further payment instructions by e-mail. Payments will be received until October 27^th.

Cancellation and refunds
Any changes and cancellations must be pre-notified in writing by email to eventos@cnpem.br. Registration fees will be refunded (50% of the amount paid) for cancellations made on or before November 5th, 2019. Cancellations made after this date are not refundable. Refunds will be made by credit card or bank transfer, depending on the original payment method.

Waiting list

The remaining places will be offered to the following applicants in the selection list.

Information for participants

General Information

• The lectures will be held at the Brazilian Biosciences National Laboratory, LNBio´s building, room 69.
• The registration fee includes all lectures, poster session, conference materials, coffee breaks and lunches on November 12^th and 13^th;
• There is no grant for transport and accommodation;
• The Workshop certificates are granted to those with a minimum of 75% attendance, and will be available after the last talk;
• Workshop contact: eventos@cnpem.br;
• Visit the Mass Spectrometry Facility website: http://lnbio.cnpem.br/facilities/mass-spectrometry/

Event Location

CNPEM – Brazilian Center for Research in Energy and Materials
Rua Giuseppe Máximo Scolfaro, 10000
Pólo II de Alta Tecnologia de Campinas
Campinas – SP – Brazil
Phone: +55 19 3512-1267
Google Maps

 

Hosting Suggestions

Here is a list of hotels and inns near the venue. The reservations and availability of rooms information is the participant’s responsibility.

 

• Matiz (Sol Inn) Barão Geraldo

Endereço: Av. Albino José Barbosa de Oliveira, 1700 – Barão Geraldo, Campinas | SP
Telefone: + 55 (19) 3749-8500
Website
Distância do local do evento: 4,4 km.

• Bristol Alphaville Campinas

Endereço: Rua Cumarú, 116 – Alphaville Industrial –  Campinas | SP – CEP: 13098-324
Telefone: (19) 3262-1525
Website
Distância do local do evento:  5 km

• Comfort Suites Campinas

Endereço: R. Embiruçu, 300 – Alphaville, Campinas | SP
Telefone: (19) 2137-9000
Website
Distância do local do evento: 5 km

• Pousada Universitária Barão Geraldo
  
  

Endereço: R. Antônio Galvão de O. Barros, 101 – Barão Geraldo – Campinas, SP CEP 13084-275
Telefone: + 55 (19) 3308-6656.
Website
Distância do local do evento: 6, 1 km

• Pousada Barão

Endereço: Av. Albino José Barbosa de Oliveira, 724 – Barão Geraldo, Campinas, SP
Telefone: (19) 3396-7060
Website
Distância do local do evento: 6,1 km

• Pousada Nova Barão

Endereço: Rua Angelo Vicentim, 1136, Barão Geraldo – Campinas, SP
Telefone: (19) 3304-1470 / mobile 98813-8640
Website
Distância do local do evento: 7,4 km

• Vitória Hotel Express Dom Pedro

Endereço: Rua Heitor Ernesto Sartori, 555 – Center Santa Genebra, Campinas, / São Paulo, Brasil
Telefone: (19) 3708-9500
Website
Distância do local do evento: 10 km

 

Guidelines for Poster Session

Guidelines for Poster Session

• Posters will be presented in the two days of the meeting, during the coffee-breaks. The day of the presentation of each participant will be available in the confirmed participants list.

• Poster layout should be a portrait, with dimension: 90 x 120 cm (width x height); with a standard channel finish;
• Posters should be written in English and the content must be related to the submitted abstract;
• There will be a board to hang your poster. Each author will be provided with one board.

 

Contact

E-mail: eventos@cnpem.br
Phone: +55 (19) 3512-1267

 

Local Committee

Adriana Franco Paes Leme
Bianca Alves Pauletti
Carolina Carnielli
Maria Livia Gonçalves
Cristiane Duarte
Murilo Oliveira

http://lnbio.cnpem.br/

http://lnbio.cnpem.br/facilities/mass-spectrometry/

In Partnership with