Opportunities and obstacles for deep learning in biology and medicine
T Ching, DS Himmelstein… - Journal of the …, 2018 - royalsocietypublishing.org
Deep learning describes a class of machine learning algorithms that are capable of
combining raw inputs into layers of intermediate features. These algorithms have recently …
combining raw inputs into layers of intermediate features. These algorithms have recently …
Deep learning in pharmacogenomics: from gene regulation to patient stratification
This Perspective provides examples of current and future applications of deep learning in
pharmacogenomics, including: identification of novel regulatory variants located in …
pharmacogenomics, including: identification of novel regulatory variants located in …
Explainable machine learning for scientific insights and discoveries
Machine learning methods have been remarkably successful for a wide range of application
areas in the extraction of essential information from data. An exciting and relatively recent …
areas in the extraction of essential information from data. An exciting and relatively recent …
DeepHINT: understanding HIV-1 integration via deep learning with attention
Motivation Human immunodeficiency virus type 1 (HIV-1) genome integration is closely
related to clinical latency and viral rebound. In addition to human DNA sequences that …
related to clinical latency and viral rebound. In addition to human DNA sequences that …
Learning, visualizing and exploring 16S rRNA structure using an attention-based deep neural network
Recurrent neural networks with memory and attention mechanisms are widely used in
natural language processing because they can capture short and long term sequential …
natural language processing because they can capture short and long term sequential …
Interpretable and predictive deep neural network modeling of the SARS-Cov-2 spike protein sequence to predict COVID-19 disease severity
BA Sokhansanj, Z Zhao, GL Rosen - Biology, 2022 - mdpi.com
Simple Summary As COVID-19 shifts from pandemic to endemic, emerging variants may be
more or less virulent. Predicting whether an emerging COVID-19 variant has of high risk of …
more or less virulent. Predicting whether an emerging COVID-19 variant has of high risk of …
Interpretable and predictive deep modeling of the SARS-CoV-2 spike protein sequence
As the COVID-19 pandemic continues, the SARS-CoV-2 virus continues to rapidly mutate
and change in ways that impact virulence, transmissibility, and immune evasion. Genome …
and change in ways that impact virulence, transmissibility, and immune evasion. Genome …
Apparatus and method for student-teacher transfer learning network using knowledge bridge
JY Kim, M El-Khamy, J Lee - US Patent 11,195,093, 2021 - Google Patents
An apparatus, a method, a method of manufacturing and apparatus, and a method of
constructing an integrated circuit are provided. The apparatus includes a teacher network; a …
constructing an integrated circuit are provided. The apparatus includes a teacher network; a …
Mapping data to deep understanding: Making the most of the deluge of SARS-CoV-2 genome sequences
BA Sokhansanj, GL Rosen - Msystems, 2022 - Am Soc Microbiol
Next-generation sequencing has been essential to the global response to the COVID-19
pandemic. As of January 2022, nearly 7 million severe acute respiratory syndrome …
pandemic. As of January 2022, nearly 7 million severe acute respiratory syndrome …