K
Krishna Kanhaiya
Researcher at Turku Centre for Computer Science
Publications - 11
Citations - 139
Krishna Kanhaiya is an academic researcher from Turku Centre for Computer Science. The author has contributed to research in topics: Network science & Network controllability. The author has an hindex of 5, co-authored 10 publications receiving 110 citations. Previous affiliations of Krishna Kanhaiya include Indian Institute of Technology Indore & Åbo Akademi University.
Papers
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Journal ArticleDOI
Controlling Directed Protein Interaction Networks in Cancer.
TL;DR: A novel and efficient approach for the (targeted) structural controllability of cancer networks and a better understanding of the control dynamics of cancer through computational modelling can pave the way for new efficient therapeutic approaches and personalized medicine.
Journal ArticleDOI
Structural Target Controllability of Linear Networks
TL;DR: It is proved here that the target controllability problem is NP-hard in all practical setups, i.e., when the control power of any individual input is bounded by some constant.
Book ChapterDOI
Target Controllability of Linear Networks
TL;DR: It is proved that the structural target controllability problem is NP-hard when looking to minimize the number of driven nodes within the network, i.e., the first set of nodes which need to be directly controlled in order to structurally control the target.
Journal ArticleDOI
Network Topologies Decoding Cervical Cancer.
TL;DR: The analysis of the protein-protein interaction networks of the uterine cervix cells for the normal and disease states found that the disease network was less random than the normal one, providing an insight into the change in complexity of the underlying network in disease state.
Journal ArticleDOI
NetControl4BioMed: a pipeline for biomedical data acquisition and analysis of network controllability
TL;DR: A novel bioinformatics data analysis pipeline called NetControl4BioMed is developed based on the concept of target structural control of linear networks for controlling and better understanding of molecular interaction networks through combinatorial multi-drug therapies, for more efficient therapeutic approaches and personalised medicine.