NIST · ИТ · 6987ad14bb541ee86c52
Interpretable modeling of genotype-phenotype landscapes with state-of-the-art predictive power
Large-scale measurements linking genetic background to biological function have drivena need for models that can incorporate these data for reliable predictions and insightinto the underlying biophysical system. Recent modeling efforts, however, prioritize
NIST · ИТОфициальный источник · 2022-06-21
{
"title_en": "Interpretable modeling of genotype-phenotype landscapes with state-of-the-art predictive power",
"designation": "",
"series": "",
"status": "",
"date": "2022-06-21",
"date_original": "June 21, 2022",
"url": "https://www.nist.gov/publications/interpretable-modeling-genotype-phenotype-landscapes-state-art-predictive-power",
"source": "NIST Publications",
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"authors_en": "Peter Tonner , Abe Pressman , David Ross",
"abstract_excerpt_en": "Large-scale measurements linking genetic background to biological function have drivena need for models that can incorporate these data for reliable predictions and insightinto the underlying biophysical system. Recent modeling efforts, however, prioritize",
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{
"title_en": "Interpretable modeling of genotype-phenotype landscapes with state-of-the-art predictive power",
"designation": "",
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"date": "2022-06-21",
"date_original": "June 21, 2022",
"url": "https://www.nist.gov/publications/interpretable-modeling-genotype-phenotype-landscapes-state-art-predictive-power",
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"authors_en": "Peter Tonner , Abe Pressman , David Ross",
"abstract_excerpt_en": "Large-scale measurements linking genetic background to biological function have drivena need for models that can incorporate these data for reliable predictions and insightinto the underlying biophysical system. Recent modeling efforts, however, prioritize"
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