Confirmed speakers

X-Meeting, BSB and Genética Drops speakers

Helder Nakaya

Hospital Israelita Albert Einstein

Network Science Applied to Health

João Meidanis

IC - Unicamp

Distinguishing tumor types using mass spectra in pediatric brain tissue

Sameer Velankar

Team leader at EBI - UK

A new era in (structural) biology - Impact of structure prediction using AI methods

Miguel Rocha

Associate Prof. at the Univ. Minho 

A sweet tale on deep learning applications to focused molecule generation

Martin Morgan

Roswell Park Comprehensive Cancer Center

How Bioconductor Advances Science

Ana Maria Benko-Iseppon

UFPE - BR

Extremophilic plants and their stunning molecules: surviving beyond the limits

Deisy Morselli Gysi

Harvard Medical School & Northeastern University

System biology symposium 

Rodrigo Juliani Siqueira Dalmolin

Bioinformatics Multidisciplinary Environment - UFRN

System biology symposium 

Rafaela Salgado Ferreira

UFMG - BR

TBA

Anna-Sophie Fiston-Lavier

University of Montpellier

TBA

Claudia Barros Monteiro Vitorello

ESALQ / USP - BR

The use of biological networks to study plant-pathogen interactions

Jessica Maria Magno

Instituto de Pesquisa Pelé Pequeno Príncipe

Lets learn R Course

Jean Silva De Souza Resende

Instituto de Pesquisa Pelé Pequeno Príncipe

Lets learn R Course

João Carlos Degraf Muzzi

Instituto de Pesquisa Pelé Pequeno Príncipe

Lets learn R Course

Mariana Boroni

Co- founder at OneSkin

Academy X Industry, and vice versa

Michelle Zibetti Tadra

Co-founder GoGenetic

Academy X Industry, and vice versa

TBA

TBA

TBA

Network Science Applied to Health

Network science is an emerging field of research that analyzes complex networks of biological data (and people). In this seminar I will show how this approach can be used for projects related to human health

program

A sweet tale on deep learning applications to focused molecule generation

In this talk, I will describe some recent work from our group on the development of deep learning approaches towards predicting the properties and activity of compounds and proteins, based on different representations and model classes from traditional machine learning and deep learning.
I will also address the development of some tools and applications of deep generative models, to create novel compounds with desired activities, and how we use multiobjective Evolutionary Computation to guide the search of these compounds towards different aims. A case study
on computationally designing novel sweeteners will be used to  illustrate the approach.

program