Tara retreat

Hi!

You've come here because of the poster. Thank you very much for being interested.

I have a brief introduction of myself here Homepage . If by chance, you have any suggestion or comment, do not hesitate to ask me, either by email or in person! 

Nicolás.

TL;DR

Currently we have an explosion in data volume. ENA for example, holds over 70 PB of raw sequence reads, doubling every 3 to 4 years, causing an exponential increase. Se we have an opportunity, like never before in history, to leverage from this enormous amount of data to reveal hidden patterns inside this raw data using AI.

First, we want to highlight how recent AI breakthroughs are delivering significant insights in the context of metagenomics, while also outperforming classical methods.

For example, DeepMicrobes, published on 2020, surpassed Kraken2 for genus taxonomic classification.

There are more examples, but I think it's clear that AI has the potential to transform the way we analyze metagenomic data.

So, what new biological questions can we tackle with these tools?

In the context of microbial evolution, what if we could forecast ecosystem changes simply by reading the language of microbial DNA?

We want to use genomic variants as 'environmental sensors', directly from sequenced data and try to track ocean-climate gradients.