Use human readable keys for the bibliography
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@ -7,7 +7,7 @@
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* Deep Learning
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** Attention is All You Need
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#+begin_src bibtex
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@article{https://doi.org/10.48550/arxiv.1706.03762,
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@article{Vaswani2017,
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doi = {10.48550/ARXIV.1706.03762},
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url = {https://arxiv.org/abs/1706.03762},
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author = {Vaswani, Ashish and Shazeer, Noam and Parmar, Niki and
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@ -178,7 +178,7 @@ A masked language model (MLM) randomly masks some of the tokens from the input,
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* Deep Learning + Biology
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** CpG Transformer for imputation of single-cell methylomes
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#+begin_src bibtex
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@article{10.1093/bioinformatics/btab746,
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@article{DeWaele2021,
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author = {De Waele, Gaetan and Clauwaert, Jim and Menschaert, Gerben
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and Waegeman, Willem},
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title = "{CpG Transformer for imputation of single-cell methylomes}",
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@ -214,7 +214,7 @@ A masked language model (MLM) randomly masks some of the tokens from the input,
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#+end_src
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** MSA Transformer
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#+begin_src bibtex
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@article {Rao2021.02.12.430858,
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@article {Rao2021,
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author = {Rao, Roshan and Liu, Jason and Verkuil, Robert and Meier,
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Joshua and Canny, John F. and Abbeel, Pieter and Sercu, Tom
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and Rives, Alexander},
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@ -443,3 +443,50 @@ A masked language model (MLM) randomly masks some of the tokens from the input,
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challenges associated with running the competition.}
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}
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#+end_src
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** Eleven grand challenges in single-cell data science
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#+begin_src bibtex
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@article{Lähnemann2020,
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author = {L{\"a}hnemann, David and K{\"o}ster, Johannes and Szczurek,
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Ewa and McCarthy, Davis J. and Hicks, Stephanie C. and
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Robinson, Mark D. and Vallejos, Catalina A. and Campbell,
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Kieran R. and Beerenwinkel, Niko and Mahfouz, Ahmed and
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Pinello, Luca and Skums, Pavel and Stamatakis, Alexandros and
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Attolini, Camille Stephan-Otto and Aparicio, Samuel and
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Baaijens, Jasmijn and Balvert, Marleen and Barbanson, Buys de
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and Cappuccio, Antonio and Corleone, Giacomo and Dutilh, Bas
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E. and Florescu, Maria and Guryev, Victor and Holmer, Rens and
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Jahn, Katharina and Lobo, Thamar Jessurun and Keizer, Emma M.
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and Khatri, Indu and Kielbasa, Szymon M. and Korbel, Jan O.
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and Kozlov, Alexey M. and Kuo, Tzu-Hao and Lelieveldt,
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Boudewijn P.F. and Mandoiu, Ion I. and Marioni, John C. and
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Marschall, Tobias and M{\"o}lder, Felix and Niknejad, Amir and
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Raczkowski, Lukasz and Reinders, Marcel and Ridder, Jeroen de
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and Saliba, Antoine-Emmanuel and Somarakis, Antonios and
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Stegle, Oliver and Theis, Fabian J. and Yang, Huan and
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Zelikovsky, Alex and McHardy, Alice C. and Raphael, Benjamin
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J. and Shah, Sohrab P. and Sch{\"o}nhuth, Alexander},
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title = {Eleven grand challenges in single-cell data science},
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journal = {Genome Biology},
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year = 2020,
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month = {Feb},
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day = 07,
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volume = 21,
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number = 1,
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pages = 31,
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abstract = {The recent boom in microfluidics and combinatorial indexing
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strategies, combined with low sequencing costs, has empowered
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single-cell sequencing technology. Thousands---or even
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millions---of cells analyzed in a single experiment amount to
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a data revolution in single-cell biology and pose unique data
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science problems. Here, we outline eleven challenges that will
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be central to bringing this emerging field of single-cell data
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science forward. For each challenge, we highlight motivating
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research questions, review prior work, and formulate open
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problems. This compendium is for established researchers,
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newcomers, and students alike, highlighting interesting and
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rewarding problems for the coming years.},
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issn = {1474-760X},
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doi = {10.1186/s13059-020-1926-6},
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url = {https://doi.org/10.1186/s13059-020-1926-6}
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}
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#+end_src
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@ -1,4 +1,4 @@
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@article{https://doi.org/10.48550/arxiv.1706.03762,
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@article{Vaswani2017,
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doi = {10.48550/ARXIV.1706.03762},
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url = {https://arxiv.org/abs/1706.03762},
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author = {Vaswani, Ashish and Shazeer, Noam and Parmar, Niki and
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@ -148,7 +148,7 @@
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copyright = {arXiv.org perpetual, non-exclusive license}
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}
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@article{10.1093/bioinformatics/btab746,
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@article{DeWaele2021,
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author = {De Waele, Gaetan and Clauwaert, Jim and Menschaert, Gerben
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and Waegeman, Willem},
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title = "{CpG Transformer for imputation of single-cell methylomes}",
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@ -182,7 +182,7 @@
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{https://academic.oup.com/bioinformatics/article-pdf/38/3/597/42167564/btab746.pdf},
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}
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@article {Rao2021.02.12.430858,
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@article {Rao2021,
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author = {Rao, Roshan and Liu, Jason and Verkuil, Robert and Meier,
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Joshua and Canny, John F. and Abbeel, Pieter and Sercu, Tom
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and Rives, Alexander},
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@ -399,3 +399,48 @@
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describe trends of well performing approaches, and discuss
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challenges associated with running the competition.}
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}
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@article{Lähnemann2020,
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author = {L{\"a}hnemann, David and K{\"o}ster, Johannes and Szczurek,
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Ewa and McCarthy, Davis J. and Hicks, Stephanie C. and
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Robinson, Mark D. and Vallejos, Catalina A. and Campbell,
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Kieran R. and Beerenwinkel, Niko and Mahfouz, Ahmed and
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Pinello, Luca and Skums, Pavel and Stamatakis, Alexandros and
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Attolini, Camille Stephan-Otto and Aparicio, Samuel and
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Baaijens, Jasmijn and Balvert, Marleen and Barbanson, Buys de
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and Cappuccio, Antonio and Corleone, Giacomo and Dutilh, Bas
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E. and Florescu, Maria and Guryev, Victor and Holmer, Rens and
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Jahn, Katharina and Lobo, Thamar Jessurun and Keizer, Emma M.
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and Khatri, Indu and Kielbasa, Szymon M. and Korbel, Jan O.
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and Kozlov, Alexey M. and Kuo, Tzu-Hao and Lelieveldt,
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Boudewijn P.F. and Mandoiu, Ion I. and Marioni, John C. and
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Marschall, Tobias and M{\"o}lder, Felix and Niknejad, Amir and
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Raczkowski, Lukasz and Reinders, Marcel and Ridder, Jeroen de
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and Saliba, Antoine-Emmanuel and Somarakis, Antonios and
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Stegle, Oliver and Theis, Fabian J. and Yang, Huan and
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Zelikovsky, Alex and McHardy, Alice C. and Raphael, Benjamin
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J. and Shah, Sohrab P. and Sch{\"o}nhuth, Alexander},
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title = {Eleven grand challenges in single-cell data science},
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journal = {Genome Biology},
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year = 2020,
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month = {Feb},
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day = 07,
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volume = 21,
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number = 1,
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pages = 31,
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abstract = {The recent boom in microfluidics and combinatorial indexing
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strategies, combined with low sequencing costs, has empowered
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single-cell sequencing technology. Thousands---or even
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millions---of cells analyzed in a single experiment amount to
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a data revolution in single-cell biology and pose unique data
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science problems. Here, we outline eleven challenges that will
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be central to bringing this emerging field of single-cell data
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science forward. For each challenge, we highlight motivating
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research questions, review prior work, and formulate open
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problems. This compendium is for established researchers,
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newcomers, and students alike, highlighting interesting and
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rewarding problems for the coming years.},
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issn = {1474-760X},
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doi = {10.1186/s13059-020-1926-6},
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url = {https://doi.org/10.1186/s13059-020-1926-6}
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}
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