Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Nonconvex Penalty Based Low-Rank Representation and Sparse Regression for eQTL Mapping. Retrieved May 24, 2026, from https://4ort.xyz/entity/nonconvex-penalty-based-low-rank-representation-and-sparse-regression-for-eqtl-mapping
MLA“Nonconvex Penalty Based Low-Rank Representation and Sparse Regression for eQTL Mapping.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/nonconvex-penalty-based-low-rank-representation-and-sparse-regression-for-eqtl-mapping.
BibTeX@misc{4ortxyz_nonconvex-penalty-based-low-rank-representation-and-sparse-regression-for-eqtl-mapping_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Nonconvex Penalty Based Low-Rank Representation and Sparse Regression for eQTL Mapping}}, year = {2026}, url = {https://4ort.xyz/entity/nonconvex-penalty-based-low-rank-representation-and-sparse-regression-for-eqtl-mapping}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Nonconvex Penalty Based Low-Rank Representation and Sparse Regression for eQTL Mapping — https://4ort.xyz/entity/nonconvex-penalty-based-low-rank-representation-and-sparse-regression-for-eqtl-mapping (retrieved 2026-05-24)
