Maxat Kulmanov
Title
Cited by
Cited by
Year
DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier
M Kulmanov, MA Khan, R Hoehndorf
Bioinformatics 34 (4), 660-668, 2018
1462018
The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens
N Zhou, Y Jiang, TR Bergquist, AJ Lee, BZ Kacsoh, AW Crocker, ...
Genome Biology 20 (244), 2019
732019
DeepGOPlus: Improved protein function prediction from sequence
M Kulmanov, R Hoehndorf
Bioinformatics, 2019
442019
Semantic prioritization of novel causative genomic variants
I Boudellioua, RBM Razali, M Kulmanov, Y Hashish, VB Bajic, ...
PLoS computational biology 13 (4), e1005500, 2017
272017
Evaluating the effect of annotation size on measures of semantic similarity
M Kulmanov, R Hoehndorf
Journal of biomedical semantics 8 (1), 1-10, 2017
222017
DeepPVP: phenotype-based prioritization of causative variants using deep learning
I Boudellioua, M Kulmanov, PN Schofield, GV Gkoutos, R Hoehndorf
BMC Bioinformatics 29 (65), 2019
202019
EL Embeddings: Geometric construction of models for the Description Logic EL++
M Kulmanov, W Liu-Wei, Y Yan, R Hoehndorf
International Joint Conferences on Artificial Intelligence Organization …, 2019
142019
Functional pangenome analysis shows key features of e protein are preserved in sars and sars-cov-2
I Alam, AA Kamau, M Kulmanov, Ł Jaremko, ST Arold, A Pain, T Gojobori, ...
Frontiers in cellular and infection microbiology 10, 405, 2020
10*2020
PathoPhenoDB, linking human pathogens to their phenotypes in support of infectious disease research
Ş Kafkas, M Abdelhakim, Y Hashish, M Kulmanov, M Abdellatif, ...
Scientific data 6 (1), 1-8, 2019
102019
Semantic similarity and machine learning with ontologies.
M Kulmanov, FZ Smaili, X Gao, R Hoehndorf
Oxford University Press (OUP), 2020
6*2020
DES-TOMATO: A Knowledge Exploration System Focused On Tomato Species
A Salhi, S Negrão, M Essack, MJL Morton, S Bougouffa, R Razali, ...
Scientific reports 7 (1), 5968, 2017
62017
OligoPVP: Phenotype-driven analysis of individual genomic information to prioritize oligogenic disease variants
I Boudellioua, M Kulmanov, PN Schofield, GV Gkoutos, R Hoehndorf
Scientific Reports 8 (1), 2045-2322, 2018
42018
Ontology-based validation and identification of regulatory phenotypes
M Kulmanov, PN Schofield, GV Gkoutos, R Hoehndorf
Bioinformatics 34 (17), 2018
42018
DeepPheno: Predicting single gene loss-of-function phenotypes using an ontology-aware hierarchical classifier
M Kulmanov, R Hoehndorf
PLoS computational biology, 2020
12020
A machine learning based approach for similarity search on biodiversity knowledge graphs
C Weiland, M Kulmanov, M Schmidt, R Hoehndorf
Pensoft Publishers, 2019
12019
Vec2SPARQL: integrating SPARQL queries and knowledge graph embeddings
M Kulmanov, S Kafkas, A Karwath, A Malic, G Gkoutos, M Dumontier, ...
Semantic Web Applications and Tools for Health Care and Life Sciences 2275, 2018
12018
Predicting Gene Functions and Phenotypes by combining Deep Learning and Ontologies
M Kulmanov
2020
Uncovering the dark matter of the metagenome one read at a time
N Dimonaco, C Creevey, R Hoehndorf, M Kulmanov, W Liuwei, A Clare, ...
Access Microbiology 1 (1A), 864, 2019
2019
Code for: Semantic prioritization of novel causative genomic variants
RB Mahamad, M Kulmanov, Y Hashish, VB Bajic, E Goncalves-Serra, ...
GitHub, 2017
2017
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Articles 1–19