Browsing Data Science Institute (Scholarly Articles) by Author "Khan, Yasar"

Now showing items 1-5 of 5

    • Abstract A27: A linked data approach to discover HPV oncoprotiens and RB1 induced mutation associations for the retinoblastoma research 

      Jha, Alokkumar; Khan, Yasar; Rebholz-Schumann, Dietrich; Sahay, Ratnesh (American Association for Cancer Research, 2017-01)
      Background: LOSS or GAIN in tumor suppressor gene RB1 play a significant role as in case of loss low penetrance where only 39% of eye at risk develops in retinoblastoma. This research covers the multiple mutation types and ...

    • A linked data visualiser for finite element biosimulations 

      Mehdi, Muntazir; Khan, Yasar; Jares, Joao; Freitas, Andre; Jha, Alok Kumar; Sakellarios, Antonis; Sahay, Ratnesh (World Scientific Publishing, 2016)
      Biosimulation models are used to understand the multiple or different causative factors that cause impairment in human organs. Finite Element Method (FEM) provide a mathematical framework to simulate dynamic biological ...

    • One size does not fit all: querying web polystores 

      Khan, Yasar; Zimmermann, Antoine; Jha, Alokkumar; Gadepally, Vijay; d'Aquin, Mathieu; Sahay, Ratnesh (IEEE, 2019-01-17)
      Data retrieval systems are facing a paradigm shift due to the proliferation of specialized data storage engines (SQL, NoSQL, Column Stores, MapReduce, Data Stream, and Graph) supported by varied data models (CSV, JSON, ...

    • SAFE: SPARQL federation over RDF data cubes with access control 

      Khan, Yasar; Saleem, Muhammad; Mehdi, Muntazir; Hogan, Aidan; Mehmood, Qaiser; Rebholz-Schuhmann, Dietrich; Sahay, Ratnesh (BioMed Central, 2017-02-01)
      Several query federation engines have been proposed for accessing public Linked Open Data sources. However, in many domains, resources are sensitive and access to these resources is tightly controlled by stakeholders; ...

    • Towards precision medicine: discovering novel gynecological cancer biomarkers and pathways using linked data 

      Jha, Alokkumar; Khan, Yasar; Mehdi, Muntazir; Karim, Md Rezaul; Mehmood, Qaiser; Zappa, Achille; Rebholz-Schuhmann, Dietrich; Sahay, Ratnesh (BioMed Central, 2017-09-19)
      Next Generation Sequencing (NGS) is playing a key role in therapeutic decision making for the cancer prognosis and treatment. The NGS technologies are producing a massive amount of sequencing datasets. Often, these datasets ...