PAIR: Reconstructing Single‐Cell Open‐Chromatin Landscapes for Transcription Factor Regulome Mapping
scATAC‐seq analysis is often constrained by limited sequencing depth, extreme sparsity, and pervasive technical missingness. PAIR is a probabilistic framework that restores scATAC‐seq accessibility profiles by directly modeling the native cell–peak bipartite structure of chromatin accessibility.
Yanchi Su +7 more
wiley +1 more source
A Deep Learning Approach for Missing Data Imputation of Rating Scales Assessing Attention-Deficit Hyperactivity Disorder. [PDF]
Cheng CY +4 more
europepmc +1 more source
NCRN Meeting Spring 2014: Imputation of multivariate continuous data with non-ignorable missingness
Thaís Paiva, Jerry Reiter
openalex +1 more source
Appendix C. Description of the missing data imputation procedure.
Viktor Nilsson‐Örtman +3 more
openalex +1 more source
ABSTRACT This paper is a formal response to the comments raised by Yiquan Wang et al. and Peikai Sun et al. on our published work entitled “GLM7–A Novel Composite Glycolipid Index Derived from Routine Health Indicators for Enhanced Diagnosis and Prediction of Multimorbidity”. We address all the comments in this response.
Zhihua Wang, Suowen Xu
wiley +1 more source
An Integrated Fuzzy C-Means Method for Missing Data Imputation Using Taxi GPS Data. [PDF]
Huang J, Mao B, Bai Y, Zhang T, Miao C.
europepmc +1 more source
A closed‐loop, data‐driven approach facilitates the exploration of high‐performance Si─Ge─Sn alloys as promising fast‐charging battery anodes. Autonomous electrochemical experimentation using a scanning droplet cell is combined with real‐time optimization to efficiently navigate composition space.
Alexey Sanin +7 more
wiley +1 more source
Transformers deep learning models for missing data imputation: an application of the ReMasker model on a psychometric scale. [PDF]
Casella M, Milano N, Dolce P, Marocco D.
europepmc +1 more source
Effect of Missing Data Imputation on Deep Learning Prediction Performance for Vesicoureteral Reflux and Recurrent Urinary Tract Infection Clinical Study. [PDF]
Köse T +4 more
europepmc +1 more source
Missing Data Imputation for Ordinal Data
Aera LeBoulluec, Maryuri Quintero
openaire +1 more source

