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ORCIDMaxat Kulmanov
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2020 – today
- 2024
[j12]Maxat Kulmanov
, Francisco J. Guzmán-Vega, Paula Duek Roggli, Lydie Lane, Stefan T. Arold, Robert Hoehndorf:
Protein function prediction as approximate semantic entailment. Nat. Mac. Intell. 6(2): 220-228 (2024)- 2023
- [j11]Fernando Zhapa-Camacho, Maxat Kulmanov, Robert Hoehndorf:
mOWL: Python library for machine learning with biomedical ontologies. Bioinform. 39(1) (2023) - 2022
- [c3]Ali Syed, Senay Kafkas, Maxat Kulmanov, Robert Hoehndorf:
Using SPARQL to Unify Queries over Data, Ontologies, and Machine Learning Models in the PhenomeBrowser Knowledgebase. SWAT4HCLS 2022: 97-102 - [i3]Xi Peng, Zhenwei Tang, Maxat Kulmanov, Kexin Niu, Robert Hoehndorf:
Description Logic EL++ Embeddings with Intersectional Closure. CoRR abs/2202.14018 (2022) - 2021
- [j10]Maxat Kulmanov, Fatima Zohra Smaili, Xin Gao, Robert Hoehndorf:
Semantic similarity and machine learning with ontologies. Briefings Bioinform. 22(4) (2021) - [j9]Maxat Kulmanov, Robert Hoehndorf:
DeepGOPlus: improved protein function prediction from sequence. Bioinform. 37(8): 1187 (2021) - [j8]Maxat Kulmanov, Fernando Zhapa-Camacho, Robert Hoehndorf:
DeepGOWeb: fast and accurate protein function prediction on the (Semantic) Web. Nucleic Acids Res. 49(Webserver-Issue): 140-146 (2021) - 2020
- [j7]Maxat Kulmanov, Robert Hoehndorf:
DeepGOPlus: improved protein function prediction from sequence. Bioinform. 36(2): 422-429 (2020) - [j6]Maxat Kulmanov, Robert Hoehndorf:
DeepPheno: Predicting single gene loss-of-function phenotypes using an ontology-aware hierarchical classifier. PLoS Comput. Biol. 16(11) (2020)
2010 – 2019
- 2019
- [j5]Imane Boudellioua, Maxat Kulmanov, Paul N. Schofield, Georgios V. Gkoutos, Robert Hoehndorf:
DeepPVP: phenotype-based prioritization of causative variants using deep learning. BMC Bioinform. 20(1): 65 (2019) - [c2]Maxat Kulmanov, Wang Liu-Wei, Yuan Yan, Robert Hoehndorf:
EL Embeddings: Geometric Construction of Models for the Description Logic EL++. IJCAI 2019: 6103-6109 - [i2]Maxat Kulmanov, Wang Liu-Wei, Yuan Yan, Robert Hoehndorf:
EL Embeddings: Geometric construction of models for the Description Logic EL ++. CoRR abs/1902.10499 (2019) - 2018
- [j4]Maxat Kulmanov, Mohammad Asif Khan, Robert Hoehndorf:
DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier. Bioinform. 34(4): 660-668 (2018) - [j3]Maxat Kulmanov, Paul N. Schofield, Georgios V. Gkoutos, Robert Hoehndorf:
Ontology-based validation and identification of regulatory phenotypes. Bioinform. 34(17): i857-i865 (2018) - [c1]Maxat Kulmanov, Senay Kafkas, Andreas Karwath, Alexander Malic, Georgios V. Gkoutos, Michel Dumontier, Robert Hoehndorf:
Vec2SPARQL: integrating SPARQL queries and knowledge graph embeddings. SWAT4LS 2018 - 2017
- [j2]Maxat Kulmanov, Robert Hoehndorf:
Evaluating the effect of annotation size on measures of semantic similarity. J. Biomed. Semant. 8(1): 7:1-7:10 (2017) - [j1]Imane Boudellioua, Rozaimi B. Mahamad Razali, Maxat Kulmanov, Yasmeen Hashish, Vladimir B. Bajic, Eva Goncalves-Serra, Nadia Schoenmakers, Georgios V. Gkoutos, Paul N. Schofield, Robert Hoehndorf:
Semantic prioritization of novel causative genomic variants. PLoS Comput. Biol. 13(4) (2017) - [i1]Maxat Kulmanov, Mohammad Asif Khan, Robert Hoehndorf:
DeepGO: Predicting protein functions from sequence and interactions using a deep ontology-aware classifier. CoRR abs/1705.05919 (2017)
Coauthor Index
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