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Pages

Posts

Drawing for Publications

10 minute read

Published:

This blogpost provides guidelines and best practices for creating figures, diagrams, and plots for scientific papers, particularly in the context of cheminformatics and related fields. The goal is to ensure that all figures are clear, consistent, and suitable for publication. This is mainly a collection of personal notes coming from experience with various tools and formats, and it is not exhaustive nor a definitive guide (I’m still learning myself!).

portfolio

Bioinformatics Course

Published:

Open in GitHub

Implementing sequence alignment, domain assignment, main chain tracing, and steric overlaps detection.

Image Analysis Course

Published:

Open in GitHub

MATLAB projects on SIFT, CNNs, image registration, and triangulation.

projects

Mapping Multiple LSTM Models on FPGAs

Published:

In this work we introduce a novel framework for mapping multiple Long Short-Term Memory (LSTM) models onto FPGA devices. The proposed approach leverages Singular Value Decomposition (SVD)-based approximation and structured pruning to optimize the execution of multiple LSTMs in parallel, significantly improving performance and memory efficiency. Our FPGA-specific accelerator design features a custom dataflow architecture with dedicated SVD and non-linear kernels to handle LSTM gate computations efficiently. The framework achieves a 3Ɨ to 5Ɨ performance increase over traditional methods, with bounded accuracy loss, making it a scalable solution for high-performance applications requiring parallel LSTM execution.

Recommended citation: Your Name, You. (2024). "Paper Title Number 3." GitHub Journal of Bugs. 1(3).', link

publications

Mapping Multiple LSTM Models on FPGAs

Published in International Conference on Field-Programmable Technology (ICFPT), 2020

Open in GitHub

This paper introduces a framework for accelerating multiple Long Short-Term Memory (LSTM) models onto FPGA devices.

Recommended citation: Ribes, S., Trancoso, P., Sourdis, I., Bouganis, C.S., "Mapping Multiple LSTM Models on FPGAs", ICFPT 2020, link

Modeling PROTAC Degradation Activity with Machine Learning

Published in Artificial Intelligence in the Life Sciences, 2024

Open in GitHub Open In Colab Open in Spaces

In this work, we propose an efficient and open-source machine learning strategy to predict the degradation activity of PROteolysis TArgeting Chimeras (PROTACs).

Recommended citation: Ribes, S., Nittinger, E., Tyrchan, C., Mercado, R., "Modeling PROTAC degradation activity with machine learning", Artificial Intelligence in the Life Sciences 2024, link

talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.