Home ›
Entities
› academia
› AIPPT: Predicts anti-inflammatory peptides using the most characteristic subset of bases and sequences by stacking ensemble learning strategies
AIPPT: Predicts anti-inflammatory peptides using the most characteristic subset of bases and sequences by stacking ensemble learning strategies
Research article (2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2023) · cited 14× · AI/ML
AIPPT: Predicts anti-inflammatory peptides using the most characteristic subset of bases and sequences by stacking ensemble learning strategies
Summary
AIPPT: Predicts anti-inflammatory peptides using the most characteristic subset of bases and sequences by stacking ensemble learning strategies is a scholarly article[1].
Key Facts
AIPPT: Predicts anti-inflammatory peptides using the most characteristic subset of bases and sequences by stacking ensemble learning strategies'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). AIPPT: Predicts anti-inflammatory peptides using the most characteristic subset of bases and sequences by stacking ensemble learning strategies. Retrieved May 24, 2026, from https://4ort.xyz/entity/aippt-predicts-anti-inflammatory-peptides-using-the-most-characteristic-subset-of-bases-and-sequences-by-stacking-ensemb
MLA“AIPPT: Predicts anti-inflammatory peptides using the most characteristic subset of bases and sequences by stacking ensemble learning strategies.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/aippt-predicts-anti-inflammatory-peptides-using-the-most-characteristic-subset-of-bases-and-sequences-by-stacking-ensemb.
BibTeX@misc{4ortxyz_aippt-predicts-anti-inflammatory-peptides-using-the-most-characteristic-subset-of-bases-and-sequences-by-stacking-ensemb_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{AIPPT: Predicts anti-inflammatory peptides using the most characteristic subset of bases and sequences by stacking ensemble learning strategies}}, year = {2026}, url = {https://4ort.xyz/entity/aippt-predicts-anti-inflammatory-peptides-using-the-most-characteristic-subset-of-bases-and-sequences-by-stacking-ensemb}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): AIPPT: Predicts anti-inflammatory peptides using the most characteristic subset of bases and sequences by stacking ensemble learning strategies — https://4ort.xyz/entity/aippt-predicts-anti-inflammatory-peptides-using-the-most-characteristic-subset-of-bases-and-sequences-by-stacking-ensemb (retrieved 2026-05-24)
