readme: update bib entry and links - GENA in NAR
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README.md
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@@ -19,7 +19,7 @@ Differences between GENA-LM (`gena-lm-bigbird-base-t2t`) and DNABERT:
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Source code and data: https://github.com/AIRI-Institute/GENA_LM
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Paper: https://
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This repository also contains models that are finetuned on downstream tasks and models that are used in our [GENA-Web](https://dnalm.airi.net) web tool for genomic sequence annotation:
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- splice sites prediction (branch [gena_web_spliceai](https://huggingface.co/AIRI-Institute/gena-lm-bigbird-base-t2t/tree/gena_web_spliceai))
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We pre-trained `gena-lm-bigbird-base-t2t` using the latest T2T human genome assembly (https://www.ncbi.nlm.nih.gov/assembly/GCA_009914755.3/). The data was augmented by sampling mutations from 1000-genome SNPs (gnomAD dataset). Pre-training was performed for 1,070,000 iterations with batch size 256.
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## Evaluation
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For evaluation results, see our paper: https://
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## Citation
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```bibtex
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@article{GENA_LM,
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}
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```
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Source code and data: https://github.com/AIRI-Institute/GENA_LM
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Paper: https://academic.oup.com/nar/article/53/2/gkae1310/7954523
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This repository also contains models that are finetuned on downstream tasks and models that are used in our [GENA-Web](https://dnalm.airi.net) web tool for genomic sequence annotation:
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- splice sites prediction (branch [gena_web_spliceai](https://huggingface.co/AIRI-Institute/gena-lm-bigbird-base-t2t/tree/gena_web_spliceai))
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We pre-trained `gena-lm-bigbird-base-t2t` using the latest T2T human genome assembly (https://www.ncbi.nlm.nih.gov/assembly/GCA_009914755.3/). The data was augmented by sampling mutations from 1000-genome SNPs (gnomAD dataset). Pre-training was performed for 1,070,000 iterations with batch size 256.
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## Evaluation
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For evaluation results, see our paper: https://academic.oup.com/nar/article/53/2/gkae1310/7954523
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## Citation
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```bibtex
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@article{GENA_LM,
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author = {Fishman, Veniamin and Kuratov, Yuri and Shmelev, Aleksei and Petrov, Maxim and Penzar, Dmitry and Shepelin, Denis and Chekanov, Nikolay and Kardymon, Olga and Burtsev, Mikhail},
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title = {GENA-LM: a family of open-source foundational DNA language models for long sequences},
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journal = {Nucleic Acids Research},
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volume = {53},
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number = {2},
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pages = {gkae1310},
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year = {2025},
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month = {01},
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issn = {0305-1048},
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doi = {10.1093/nar/gkae1310},
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url = {https://doi.org/10.1093/nar/gkae1310},
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eprint = {https://academic.oup.com/nar/article-pdf/53/2/gkae1310/61443229/gkae1310.pdf},
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}
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```
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