https://www.biorxiv.org/content/10.1101/2020.10.25.353946v1

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Issue used to develop reference extraction workflow

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The new issue has title My new issue.

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The new issue has title My new issue with updated title. Line 1\n Line 2\n

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The new issue has title My new issue with title v4.

1. Neural networks to learn protein sequence-function relationships from deep mutational scanning data Sam Gelman, Philip A. Romero, Anthony Gitter bioRxiv (2020-10-25) https://www.biorxiv.org/content/10.1101/2020.10.25.353946v1 DOI: 10.1101/2020.10.25.353946

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The new issue has title My new issue with title v5.

1. Neural networks to learn protein sequence-function relationships from deep mutational scanning data Sam Gelman, Philip A. Romero, Anthony Gitter bioRxiv (2020-10-25) https://www.biorxiv.org/content/10.1101/2020.10.25.353946v1 DOI: 10.1101/2020.10.25.353946

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The new issue has title My new issue with title v7.

1. Neural networks to learn protein sequence-function relationships from deep mutational scanning data Sam Gelman, Philip A. Romero, Anthony Gitter bioRxiv (2020-10-25) https://www.biorxiv.org/content/10.1101/2020.10.25.353946v1 DOI: 10.1101/2020.10.25.353946

[github-actions[bot]]

The new issue has title https://www.biorxiv.org/content/10.1101/2020.10.25.353946v1.

1. Neural networks to learn protein sequence-function relationships from deep mutational scanning data Sam Gelman, Philip A. Romero, Anthony Gitter bioRxiv (2020-10-25) https://www.biorxiv.org/content/10.1101/2020.10.25.353946v1 DOI: 10.1101/2020.10.25.353946

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The new issue has title https://www.biorxiv.org/content/10.1101/2020.10.28.359828v1.

1. Neural networks to learn protein sequence-function relationships from deep mutational scanning data Sam Gelman, Philip A. Romero, Anthony Gitter bioRxiv (2020-10-25) https://www.biorxiv.org/content/10.1101/2020.10.25.353946v1 DOI: 10.1101/2020.10.25.353946

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Reference extracted for https://www.biorxiv.org/content/10.1101/2020.10.25.353946v1:

1. Neural networks to learn protein sequence-function relationships from deep mutational scanning data Sam Gelman, Philip A. Romero, Anthony Gitter bioRxiv (2020-10-25) https://www.biorxiv.org/content/10.1101/2020.10.25.353946v1 DOI: 10.1101/2020.10.25.353946

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Reference extracted for doi:10.1101/2020.10.25.353946:

1. Neural networks to learn protein sequence-function relationships from deep mutational scanning data Sam Gelman, Philip A. Romero, Anthony Gitter Cold Spring Harbor Laboratory (2020-10-25) https://doi.org/ghg83c DOI: 10.1101/2020.10.25.353946

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Reference extracted for doi:10.1038/s41592-019-0496-6:

1. Machine-learning-guided directed evolution for protein engineering Kevin K. Yang, Zachary Wu, Frances H. Arnold Nature Methods (2019-07-15) https://doi.org/gf43h4 DOI: 10.1038/s41592-019-0496-6 · PMID: 31308553

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Reference extracted for https://doi.org/10.1038/s41592-019-0496-6: Machine-learning-guided directed evolution for protein engineering Kevin K. Yang, Zachary Wu, Frances H. Arnold Nature Methods, August 2019, https://www.nature.com/articles/s41592-019-0496-6 DOI: 10.1038/s41592-019-0496-6

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Reference extracted for doi:10.1038/s41592-019-0496-6:

Machine-learning-guided directed evolution for protein engineering Kevin K. Yang, Zachary Wu, Frances H. Arnold Nature Methods, July 2019, https://doi.org/gf43h4 DOI: 10.1038/s41592-019-0496-6 · PMID: 31308553

copy/paste as

**Machine-learning-guided directed evolution for protein engineering** 
Kevin K. Yang, Zachary Wu, Frances H. Arnold 
*Nature Methods*, July 2019, <https://doi.org/gf43h4> 
DOI: [10.1038/s41592-019-0496-6](https://doi.org/10.1038/s41592-019-0496-6) · PMID: [31308553](https://www.ncbi.nlm.nih.gov/pubmed/31308553)

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Reference extracted for https://www.biorxiv.org/content/10.1101/2020.10.25.353946v1:

Neural networks to learn protein sequence-function relationships from deep mutational scanning data Sam Gelman, Philip A. Romero, Anthony Gitter bioRxiv, October 2020, https://www.biorxiv.org/content/10.1101/2020.10.25.353946v1 DOI: 10.1101/2020.10.25.353946

copy/paste as

**Neural networks to learn protein sequence-function relationships from deep mutational scanning data** 
Sam Gelman, Philip A. Romero, Anthony Gitter 
*bioRxiv*, October 2020, <https://www.biorxiv.org/content/10.1101/2020.10.25.353946v1> 
DOI: [10.1101/2020.10.25.353946](https://doi.org/10.1101/2020.10.25.353946)