[HTML][HTML] Enabling technology and core theory of synthetic biology
Synthetic biology provides a new paradigm for life science research (“build to learn”) and
opens the future journey of biotechnology (“build to use”). Here, we discuss advances of …
opens the future journey of biotechnology (“build to use”). Here, we discuss advances of …
Handling missing values in healthcare data: A systematic review of deep learning-based imputation techniques
Objective The proper handling of missing values is critical to delivering reliable estimates
and decisions, especially in high-stakes fields such as clinical research. In response to the …
and decisions, especially in high-stakes fields such as clinical research. In response to the …
Self-training: A survey
Semi-supervised algorithms aim to learn prediction functions from a small set of labeled
observations and a large set of unlabeled observations. Because this framework is relevant …
observations and a large set of unlabeled observations. Because this framework is relevant …
[HTML][HTML] Transformer for gene expression modeling (T-GEM): an interpretable deep learning model for gene expression-based phenotype predictions
Simple Summary Cancer is the second leading cause of death worldwide. Predicting
phenotype and understanding makers that define the phenotype are important tasks. We …
phenotype and understanding makers that define the phenotype are important tasks. We …
How well does gpt-4v (ision) adapt to distribution shifts? a preliminary investigation
In machine learning, generalization against distribution shifts--where deployment conditions
diverge from the training scenarios--is crucial, particularly in fields like climate modeling …
diverge from the training scenarios--is crucial, particularly in fields like climate modeling …
[HTML][HTML] Nanomedicine ex machina: between model-informed development and artificial intelligence
M Villa Nova, TP Lin, S Shanehsazzadeh… - Frontiers in Digital …, 2022 - frontiersin.org
Today, a growing number of computational aids and simulations are shaping model-
informed drug development. Artificial intelligence, a family of self-learning algorithms, is only …
informed drug development. Artificial intelligence, a family of self-learning algorithms, is only …
PERCEPTION predicts patient response and resistance to treatment using single-cell transcriptomics of their tumors
Tailoring optimal treatment for individual cancer patients remains a significant challenge. To
address this issue, we developed PERCEPTION (PERsonalized Single-Cell Expression …
address this issue, we developed PERCEPTION (PERsonalized Single-Cell Expression …
Cryptic mutations of PLC family members in brain disorders: recent discoveries and a deep-learning-based approach
Phospholipase C (PLC) is an essential isozyme involved in the phosphoinositide signalling
pathway, which maintains cellular homeostasis. Gain-and loss-of-function mutations in PLC …
pathway, which maintains cellular homeostasis. Gain-and loss-of-function mutations in PLC …
Classifying High-Risk Patients for Persistent Opioid Use After Major Spine Surgery: A Machine-Learning Approach
S Simpson, W Zhong, S Mehdipour… - Anesthesia & …, 2024 - journals.lww.com
BACKGROUND: Persistent opioid use is a common occurrence after surgery and prolonged
exposure to opioids may result in escalation and dependence. The objective of this study …
exposure to opioids may result in escalation and dependence. The objective of this study …
Finding new analgesics: Computational pharmacology faces drug discovery challenges
Despite the worldwide prevalence and huge burden of pain, pain is an undertreated
phenomenon. Currently used analgesics have several limitations regarding their efficacy …
phenomenon. Currently used analgesics have several limitations regarding their efficacy …