Results 121 to 130 of about 617,908 (340)

Interpretation of chemical reaction yields with graph neural additive network

Machine Learning: Science and Technology
Prediction of chemical yields is crucial for exploring untapped chemical reactions and optimizing synthetic pathways for targeted compounds. Recently, graph neural networks have proven successful in achieving high predictive accuracy.
Youngchun Kwon, Yongsik Jung, Youn-Suk Choi, Seokho Kang   +3 more
doaj   +1 more source

Identifiability of linear noise approximation models of chemical reaction networks from stationary distributions [PDF]

, 2022
Theodore W. Grunberg, Domitilla Del Vecchio   +1 more
openalex   +1 more source

ABC(SMC)$$^2$$: Simultaneous Inference and Model Checking of Chemical Reaction Networks [PDF]

, 2020
We present an approach that simultaneously infers model parameters while statistically verifying properties of interest to chemical reaction networks, which we observe through data and we model as parametrised continuous-time Markov Chains. The new approach simultaneously integrates learning models from data, done by likelihood-free Bayesian inference,
Molyneux, GW, Abate, A
openaire   +3 more sources

Circulating histones as clinical biomarkers in critically ill conditions

FEBS Letters, EarlyView.
Circulating histones are emerging as promising biomarkers in critical illness due to their diagnostic, prognostic, and therapeutic potential. Detection methods such as ELISA and mass spectrometry provide reliable approaches for quantifying histone levels in plasma samples.
José Luis García‐Gimenez, Juan Carlos Ruiz‐Rodríguez, Ricard Ferrer, Raquel Durá, Antonio Artigas, Iván Bajaña, David Bolado López de Andujar, Irene Cánovas‐Cervera, Adrián Ceccato, Luis Chiscano‐Camón, Elena Climent‐Martinez, Georgia García Fernández, Gemma Goma, Verónica Monforte, Beatriz Quevedo‐Sánchez, Adolf Ruiz‐Sanmartín, Antonio Sierra‐Rivera, Nieves Carbonell Monleón   +17 more
wiley   +1 more source

Real-Time Optimization and Control of Nonlinear Processes Using Machine Learning

Mathematics, 2019
Machine learning has attracted extensive interest in the process engineering field, due to the capability of modeling complex nonlinear process behavior. This work presents a method for combining neural network models with first-principles models in real-
Zhihao Zhang, Zhe Wu, David Rincon, Panagiotis D. Christofides   +3 more
doaj   +1 more source

Unlocking the potential of tumor‐derived DNA in urine for cancer detection: methodological challenges and opportunities

Molecular Oncology, EarlyView.
Urine is a rich source of biomarkers for cancer detection. Tumor‐derived material is released into the bloodstream and transported to the urine. Urine can easily be collected from individuals, allowing non‐invasive cancer detection. This review discusses the rationale behind urine‐based cancer detection and its potential for cancer diagnostics ...
Birgit M. M. Wever, Renske D. M. Steenbergen   +1 more
wiley   +1 more source

Surfaceome: a new era in the discovery of immune evasion mechanisms of circulating tumor cells

Molecular Oncology, EarlyView.
In the era of immunotherapies, many patients either do not respond or eventually develop resistance. We propose to pave the way for proteomic analysis of surface‐expressed proteins called surfaceome, of circulating tumor cells. This approach seeks to identify immune evasion mechanisms and discover potential therapeutic targets. Circulating tumor cells (
Doryan Masmoudi, Jérome Vialaret, Christophe Hirtz, Catherine Alix‐Panabières   +3 more
wiley   +1 more source

Cell‐free and extracellular vesicle microRNAs with clinical utility for solid tumors

Molecular Oncology, EarlyView.
Cell‐free microRNAs (cfmiRs) are small‐RNA circulating molecules detectable in almost all body biofluids. Innovative technologies have improved the application of cfmiRs to oncology, with a focus on clinical needs for different solid tumors, but with emphasis on diagnosis, prognosis, cancer recurrence, as well as treatment monitoring.
Yoshinori Hayashi, Janelle‐Cheri Millen, Romela Irene Ramos, Jennifer A. Linehan, Timothy G. Wilson, Dave S. B. Hoon, Matias A. Bustos   +6 more
wiley   +1 more source

Molecular Codes in Biological and Chemical Reaction Networks

PLoS ONE, 2013
Shannon’s theory of communication has been very successfully applied for the analysis of biological information. However, the theory neglects semantic and pragmatic aspects and thus cannot directly be applied to distinguish between (bio-) chemical ...
D. Görlich, P. Dittrich
semanticscholar   +1 more source

Peripheral blood proteome biomarkers distinguish immunosuppressive features of cancer progression

Molecular Oncology, EarlyView.
Immune status significantly influences cancer progression. This study used plasma proteomics to analyze benign 67NR and malignant 4T1 breast tumor models at early and late tumor stages. Immune‐related proteins–osteopontin (Spp1), lactotransferrin (Ltf), calreticulin (Calr) and peroxiredoxin 2 (Prdx2)–were associated with systemic myeloid‐derived ...
Yeon Ji Park, Jae Won Oh, Hyewon Chung, Jung Won Kwon, Yi Rang Na, Kwang Pyo Kim, Seung Hyeok Seok   +6 more
wiley   +1 more source