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Found 13 papers, 8 papers with code
Product Manifold Representations for Learning on Biological Pathways
Machine learning models that embed graphs in non-Euclidean spaces have shown substantial benefits in a variety of contexts, but their application has not been studied extensively in the biological domain, particularly with respect to biological pathway graphs.
Current and future directions in network biology
As such, it is expected to help shape short- and long-term vision for future computational and algorithmic research in network biology.
A Text-guided Protein Design Framework
Current AI-assisted protein design mainly utilizes protein sequential and structural information.
Graph algorithms for predicting subcellular localization at the pathway level
Protein subcellular localization is an important factor in normal cellular processes and disease.
The Coming of Age of Nucleic Acid Vaccines during COVID-19
During the COVID-19 pandemic, these DNA and RNA vaccines have facilitated the development and deployment of vaccines at an unprecedented pace.
Application of Traditional Vaccine Development Strategies to SARS-CoV-2
Subunit vaccines contain instead an isolated, immunogenic component of the virus.
Molecular and Serologic Diagnostic Technologies for SARS-CoV-2
These two categories of tests provide different perspectives valuable to understanding the spread of SARS-CoV-2.
Ten Quick Tips for Deep Learning in Biology
In particular, machine learning is concerned with the development and applications of algorithms that can recognize patterns in data and use them for predictive modeling.
Identification and Development of Therapeutics for COVID-19
A number of potential therapeutics against SARS-CoV-2 and the resultant COVID-19 illness were rapidly identified, leading to a large number of clinical trials investigating a variety of possible therapeutic approaches being initiated early on in the pandemic.
Pathogenesis, Symptomatology, and Transmission of SARS-CoV-2 through Analysis of Viral Genomics and Structure
While this viral species was unknown prior to January 2020, its similarity to other coronaviruses that infect humans has allowed for rapid insight into the mechanisms that it uses to infect human hosts, as well as the ways in which the human immune system can respond.
Bayes Optimal Informer Sets for Early-Stage Drug Discovery
An IBR method selects an informer set of compounds, and then prioritizes the remaining compounds on the basis of new bioactivity experiments performed with the informer set on the target.
Methodology
Inferring Signaling Pathways with Probabilistic Programming
We build on past works that formulate signaling pathway inference as a Dynamic Bayesian Network structure estimation problem on phosphoproteomic time course data.
Unsupervised learning of transcriptional regulatory networks via latent tree graphical models
We use a latent tree graphical model to analyze gene expression without relying on transcription factor expression as a proxy for regulator activity.
