Spaces:
Sleeping
Sleeping
info_text = (""" | |
<div style="text-align: justify"> | |
This application enables to inspect mutational effects on a | |
predefined protein sequence.<br> | |
<br> | |
</div> | |
<div style="text-align: justify"> | |
It is built on the Prot-xLSTM backbone model, an xLSTM model specifically | |
trained on protein sequences. Prot-xLSTM was trained using the | |
Fill-In-the-Middle (FIM) objective, which allows it to perform sequence | |
inpainting. Additionally, the model can be provided with a potentially | |
large set of homologous sequences to enhance its predictions.<br> | |
<br> | |
</div> | |
<div style="text-align: justify"> | |
For further information please refer, to: <a href="https://openreview.net/forum?id=IjbXZdugdj" target="_blank">https://openreview.net/forum?id=IjbXZdugdj</a>. <br> | |
<br> | |
This Hugging Face application is based on the following GitHub repository: | |
<a href="https://github.com/ml-jku/Prot-xLSTM?tab=readme-ov-file" target="_blank">https://github.com/ml-jku/Prot-xLSTM?tab=readme-ov-file</a>. <br> | |
The streamlit application was developed by Elias Bürger. | |
</div> | |
<div style="text-align: justify"> | |
Please cite us as follows: <br> | |
</div> | |
""") | |
citation_text = """ | |
@misc{ | |
schmidinger2024bioxlstmgenerativemodelingrepresentation, | |
title={Bio-xLSTM: Generative modeling, representation and in-context learning of biological and chemical sequences}, | |
author={Niklas Schmidinger and Lisa Schneckenreiter and Philipp Seidl and Johannes Schimunek and Pieter-Jan Hoedt and Johannes Brandstetter and Andreas Mayr and Sohvi Luukkonen and Sepp Hochreiter and Günter Klambauer}, | |
year={2024}, | |
eprint={2411.04165}, | |
archivePrefix={arXiv}, | |
primaryClass={q-bio.BM}, | |
url={https://arxiv.org/abs/2411.04165}, | |
} | |
""" |