Home ›
Entities
› academia
› Modeling positional effects of regulatory sequences with spline transformations increases prediction accuracy of deep neural networks
Modeling positional effects of regulatory sequences with spline transformations increases prediction accuracy of deep neural networks
Research article (Bioinformatics, 2017) · cited 37× · AI/ML
Modeling positional effects of regulatory sequences with spline transformations increases prediction accuracy of deep neural networks
Summary
Modeling positional effects of regulatory sequences with spline transformations increases prediction accuracy of deep neural networks is a scholarly article[1].
Key Facts
Modeling positional effects of regulatory sequences with spline transformations increases prediction accuracy of deep neural networks's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
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). Modeling positional effects of regulatory sequences with spline transformations increases prediction accuracy of deep neural networks. Retrieved May 24, 2026, from https://4ort.xyz/entity/modeling-positional-effects-of-regulatory-sequences-with-spline-transformations-increases-prediction-accuracy-of-deep-ne
MLA“Modeling positional effects of regulatory sequences with spline transformations increases prediction accuracy of deep neural networks.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/modeling-positional-effects-of-regulatory-sequences-with-spline-transformations-increases-prediction-accuracy-of-deep-ne.
BibTeX@misc{4ortxyz_modeling-positional-effects-of-regulatory-sequences-with-spline-transformations-increases-prediction-accuracy-of-deep-ne_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Modeling positional effects of regulatory sequences with spline transformations increases prediction accuracy of deep neural networks}}, year = {2026}, url = {https://4ort.xyz/entity/modeling-positional-effects-of-regulatory-sequences-with-spline-transformations-increases-prediction-accuracy-of-deep-ne}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Modeling positional effects of regulatory sequences with spline transformations increases prediction accuracy of deep neural networks — https://4ort.xyz/entity/modeling-positional-effects-of-regulatory-sequences-with-spline-transformations-increases-prediction-accuracy-of-deep-ne (retrieved 2026-05-24)