ORCID Profile
0000-0003-3888-6495
Current Organisations
Freelance
,
Institution of Research and Community Service Unilak
,
University of Cambridge
,
Simon Fraser University
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Publications
immuneML: an ecosystem for machine learning analysis of adaptive immune receptor repertoires
Publisher: Cold Spring Harbor Laboratory
Date: 09-03-2021
DOI: 10.1101/2021.03.08.433891
Abstract: Adaptive immune receptor repertoires (AIRR) are key targets for biomedical research as they record past and ongoing adaptive immune responses. The capacity of machine learning (ML) to identify complex discriminative sequence patterns renders it an ideal approach for AIRR-based diagnostic and therapeutic discovery. To date, widespread adoption of AIRR ML has been inhibited by a lack of reproducibility, transparency, and interoperability. immuneML ( immuneml.uio.no ) addresses these concerns by implementing each step of the AIRR ML process in an extensible, open-source software ecosystem that is based on fully specified and shareable workflows. To facilitate widespread user adoption, immuneML is available as a command-line tool and through an intuitive Galaxy web interface, and extensive documentation of workflows is provided. We demonstrate the broad applicability of immuneML by (i) reproducing a large-scale study on immune state prediction, (ii) developing, integrating, and applying a novel method for antigen specificity prediction, and (iii) showcasing streamlined interpretability-focused benchmarking of AIRR ML.
Adaptive Immune Receptor Repertoire Community recommendations for sharing immune-repertoire sequencing data
Publisher: Springer Science and Business Media LLC
Date: 16-11-2017
DOI: 10.1038/NI.3873
AIRR Community Standardized Representations for Annotated Immune Repertoires
Publisher: Frontiers Media SA
Date: 28-09-2018
iReceptor: A case study in the importance of standards for data sharing
Publisher: Open Science Framework
Date: 2019
Mitigating the Effects of Cyberbullying Crime: A Multi-Faceted Solution across Disciplines
Publisher: Innovative Research Publishing
Date: 19-12-2022
DOI: 10.53894/IJIRSS.V6I1.1079
Abstract: The issue of cyberbullying is a social concern that has arisen due to the prevalent use of computer technology today. The objective of the present paper is to reveal a multi-faceted solution to cyberbullying across disciplines to mitigate the effects of this social problem. The purpose of this present study is to explore how researchers fight against cyberbullying across disciplines to create a systematic approach based on the primary health care approach based on the World Health Organization’s standard operating procedure, which consists of five types of primary care. This study is designed as a systematic literature review using Publish or Perish to automatically search through multiple databases to present the results of the keyword-based search and NVivo 12 to help understand the context. The study also uses conventional content analysis to categorize the areas of discipline and analyze the types of solutions offered in the collected 427 research articles on cyberbullying. Results have revealed that the largest major area is psychology, followed by IT media, education, and linguistics. The solutions recommended in the psychology area “plays” with a rehabilitative type of solution for cyberbullying IT media solutions are largely the preventive type the education area dominantly promotes “cyberkindness” to combat cyberbullying, and the linguistics area gives solutions that are curative for those involved in cyberbullying acts. Therefore, this research offers “beyond pre-venting” and might be the first study to recommend that WHO primary care can be used as systematic (four) steps to fight against cyberbullying.
iReceptor: A platform for querying and analyzing antibody/B-cell and T-cell receptor repertoire data across federated repositories
Publisher: Wiley
Date: 26-06-2018
DOI: 10.1111/IMR.12666
Related Organisations
Institution Of Research And Community Service Unilak
Location: Indonesia
University Of Cambridge
Location: United Kingdom of Great Britain and Northern Ireland
Related Funding Activities
Immune Receptor Repertoire Data Commons For Personalized Immunotherapy
Start Date: 2016
End Date: 2022
Funder: Canada Foundation for Innovation
View Funded ActivityArchitecture And Tools For The Query Of Antibody And T-cell Receptor Sequencing Data Repositories For Enabling Improved Personalized Medicine And Immunotherapy
Start Date: 2018
End Date: 2022
Funder: Canadian Institutes of Health Research
View Funded ActivityArchitecture And Tools For The Query Of Antibody And T-cell Receptor Sequencing Data Repositories For Enabling Improved Personalised Medicine And Immunotherapy
Start Date: 2019
End Date: 2022
Funder: European Commission
View Funded Activity