定量方法
Understanding how residue variations affect protein stability is crucial for designing functional proteins and deciphering the molecular mechanisms underlying disease-related mutations. Recent advances in protein language models (PLMs) have…
Recently, therapeutic peptides have demonstrated great promise for cancer treatment. To explore powerful anticancer peptides, artificial intelligence (AI)-based approaches have been developed to systematically screen potential candidates.…
Single-molecule RNA imaging has been made possible with the recent advances in microscopy methods. However, systematic analysis of these images has been challenging due to the highly variable background noise, even after applying…
We propose a hierarchical protein backbone generative model that separates coarse and fine-grained details. Our approach called LSD consists of two stages: sampling latents which are decoded into a contact map then sampling atomic…
Motivation: The visualization and analysis of high-dimensional data are essential in biomedical research. There is a need for secure, scalable, and reproducible tools to facilitate data exploration and interpretation. Results: We introduce…
A new strategy was developed to investigate the effect of volatile fatty acids (VFAs) on the efficiency of biogas production with a focus on improving bio-H$_2$. The inoculum used, anaerobic granular sludge obtained from a UASB reactor…
Understanding how animals make foraging decisions in challenging or unpleasant contexts sheds light on the processes that underlie cognitive development and the evolution of adaptive foraging techniques in complex ecological settings. In…
This study investigates the incidence and age at diagnosis of Non-Hodgkin Lymphoma (NHL) among missileers stationed at Malmstrom Air Force Base (MAFB) compared to national benchmarks. The analysis was motivated by reports of elevated cancer…
OLAF (Open Life Science Analysis Framework) is an open-source platform that enables researchers to perform bioinformatics analyses using natural language. By combining large language models (LLMs) with a modular agent-pipe-router…
Background Identifying the right cut-off for continuous biomarkers in clinical trials is important to identify subgroups of patients who are at greater risk of disease or more likely to benefit from a drug. The literature in this area tends…
Cells actively regulate their size during the cell cycle to maintain volume homeostasis across generations. While various mathematical models of cell size regulation have been proposed to explain how this is achieved, relating these models…
Increasingly, experimentalists and modellers alike have come to recognise the important role of spatial structure in infection dynamics. Almost invariably, spatial computational models of viral infections - as with in vitro experimental…
This study developed an accurate artificial intelligence model for predicting future height in children and adolescents using anthropometric and body composition data from the GP Cohort Study (588,546 measurements from 96,485 children aged…
Cancer remains a leading global health challenge and a major cause of mortality. This study leverages machine learning (ML) to predict the survivability of cancer patients with metastatic patterns using the comprehensive MSK-MET dataset,…
To discover new drugs is to seek and to prove causality. As an emerging approach leveraging human knowledge and creativity, data, and machine intelligence, causal inference holds the promise of reducing cognitive bias and improving decision…
Objective: To analyze the frequency and co-occurrence of dermoscopic patterns in BCC lesions and their relationship with histopathologic subtypes, using statistical analysis and Information Theory tools such as entropy, conditional entropy,…
Biochemical reaction models describing subcellular processes generally come with a large uncertainty. To be able to account for this during the modeling process, we have developed the R-package UQSA, performing uncertainty quantification…
A physics-informed neural network (PINN) embedded with the susceptible-infected-removed (SIR) model is devised to understand the temporal evolution dynamics of infectious diseases. Firstly, the effectiveness of this approach is demonstrated…
This study forms the basis of a digital twin system of the knee joint, using advanced quantitative MRI (qMRI) and machine learning to advance precision health in osteoarthritis (OA) management and knee replacement (KR) prediction. We…
Managing Type 1 diabetes (T1D) aims to optimize glucose levels within the target range while minimizing hyperglycemia and hypoglycemia. Exercise presents additional challenges due to complex effects on glucose dynamics. Despite advancements…