Results 111 to 120 of about 161,037 (263)

Missing data imputation techniques for wireless continuous vital signs monitoring. [PDF]

J Clin Monit Comput, 2023
van Rossum MC, da Silva PMA, Wang Y, Kouwenhoven EA, Hermens HJ.   +4 more
europepmc   +1 more source

SPADE: A Deep Learning Framework for Spatial Mapping and Quantitative Cell–Cell Interaction Inference

Advanced Science, EarlyView.
SPADE integrates spatial transcriptomics with single‐cell RNA sequencing by using cell–cell communications (CCC) as a guide for spatial mapping. It improves cell‐type localization, enhances sparse gene‐expression signals, and reveals CCC programs at single‐spot resolution.
Xinyi Li, Ning Zhang, Zijie Jin
wiley   +1 more source

gcimpute: A Package for Missing Data Imputation

Journal of Statistical Software
This article introduces the Python package gcimpute for missing data imputation. gcimpute can impute missing data with many different variable types, including continuous, binary, ordinal, count, and truncated values, by modeling data as samples from a Gaussian copula model. This semiparametric model learns the marginal distribution of each variable to
Yuxuan Zhao, Madeleine Udell
openaire   +4 more sources

A simulation study on missing data imputation for dichotomous variables using statistical and machine learning methods. [PDF]

Sci Rep, 2023
Ge Y, Li Z, Zhang J.
europepmc   +1 more source

Adipocyte Myoglobin Is a Determinant of Energy Expenditure and a Potential Target to Limit Obesity

Advanced Science, EarlyView.
Myoglobin, known as a muscle oxygen‐carrying protein, is shown to play a key role in fat cells that burn energy. Loss of myoglobin reduces the body's ability to generate heat and increases obesity risk, while restoring it improves metabolism. The study identifies myoglobin as a regulator of fat burning and a potential target to enhance energy ...
Christian Strehlau, Helen Broghammer, Claudia Gebhardt, Anne Hoffmann, Tobias Hagemann, Şeyma Midilli, Rachel S. Zimmer, Kristin Schubert, Vasiliki Karagiannakou, Anastasia Georgiadi, Mario Ost, Martin Krüger, Lisa Roth, Kerstin Krause, Nora Klöting, Maria Keller, Martin Wabitsch, Rima Nuwayhid, Roland H. Stimson, Michael Stumvoll, Matthias Blüher, Juliane Weiner, John T. Heiker   +22 more
wiley   +1 more source

Correcting Apparent Priming Bias Unveils Fertilizer Nitrogen‐Risk Archetypes of Surplus and Depletion Across Asian Rice Systems

Advanced Science, EarlyView.
Correcting the apparent priming effect resolves systematic biases in Asian rice fertilizer nitrogen accounting. Net soil retention drops below 7%, while 48% of fertilizer escapes, inflicting US$98.53 billion in annual reactive‐nitrogen damages. High‐resolution mapping uncovers N‐risk archetypes across 42% of the rice area, delivering a spatially ...
Xiuyun Liu, Siyuan Cai, Longlong Xia, Jagdish K. Ladha, Xiaoyuan Yan, Xu Zhao   +5 more
wiley   +1 more source

Cyclical hybrid imputation technique for missing values in data sets

Scientific Reports
The problem of missing data in data sets is the most important first step to be addressed in the preprocessing phase. Because incorrect imputation of missing data increases the error in the modeling phase and reduces the prediction performance of the ...
Kurban Kotan, Serdar Kırışoğlu
doaj   +1 more source

Strategies for data normalization and missing data imputation and consequences for potential diagnostic microRNA biomarkers in epithelial ovarian cancer. [PDF]

PLoS One, 2023
Lopacinska-Jørgensen J, Petersen PHD, Oliveira DVNP, Høgdall CK, Høgdall EV.   +4 more
europepmc   +1 more source

The KIF6‐RBP Complex Orchestrates mRNA Transport Required for Sperm Flagellar Assembly

Advanced Science, EarlyView.
Two homozygous deleterious KIF6 variants are identified in unrelated men with impaired sperm motility. Mouse models and multi‐omics analyses reveal that KIF6 cooperates with the RNA‐binding proteins FMRP and FXR1 to deliver mRNAs essential for sperm flagellar assembly, linking disrupted mRNA transport to reduced abundance of key structural and ...
Chunbo Xie, Sibing Yi, Xinle Lin, Shen Zhang, Weili Wang, Shimin Yuan, Lanlan Meng, Yong Li, Chen Tan, Chunjia Wei, Yanyan Yu, Yaoqiong Liang, Huan Zhang, Liang Hu, Guangxiu Lu, Wenbin He, Qianjun Zhang, Juan Du, Ge Lin, Chaofeng Tu, Yue‐Qiu Tan   +20 more
wiley   +1 more source

Evaluating the state of the art in missing data imputation for clinical data. [PDF]

Brief Bioinform, 2022
Luo Y.
europepmc   +1 more source