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HEALTH BELIEFS OF WOMEN SUFFERING FROM CANCER: A HOSPITAL BASED STUDY
Examination of health beliefs of women with cervical and breast cancer and its association with the socioeconomic- demographic profile of patients reveals that personal factors and supernatural causes were more stronglyrepresented in the belief system of patients.
Understanding cancer complexome using networks, spectral graph theory and multilayer framework
- A. Rai, P. Pradhan, Jyothi Nagraj, K. Lohitesh, Rajdeep Chowdhury, S. Jalan
- BiologyScientific reports
- 23 January 2017
This novel approach helps in understanding cancer at the fundamental level and provides a clue to develop promising and nascent concept of single drug therapy for multiple diseases as well as personalized medicine.
Randomness and preserved patterns in cancer network
The analysis of the breast cancer network and its normal counterpart at the proteomic level provides a benchmark for designing drugs which can target a subgraph instead of individual proteins.
Dissortativity and duplications in oral cancer
Analysis of protein-protein interaction network for the normal and oral cancer tissue and detect crucial changes in the structural properties of the networks in terms of the interactions of the hub proteins and the degree-degree correlations provides insight to the complexity of the underlying system.
Network Topologies Decoding Cervical Cancer
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.
SIFT-FANN: An efficient framework for spatio-spectral fusion of satellite images
- Kunal Kumar Rai, A. Rai, K. Dhar, J. Senthilnath, S. N. Omkar, Ramesh K.N
- Mathematics, Environmental ScienceJournal of the Indian Society of Remote Sensing
- 1 February 2017
The results show that the quality of fused images obtained using the Fast Approximate Nearest Neighbor (FANN) algorithm is computationally efficient.
Network spectra for drug-target identification in complex diseases: new guns against old foes
In this review, rapid advancements in the field of network science in combination with spectral graph theory that enables us to uncover the complexities of various diseases are illustrated.
Prognostic interaction patterns in diabetes mellitus II: A random-matrix-theory relation.
This work analyzes protein-protein interactions in diabetes mellitus II and its normal counterpart under the combined framework of random matrix theory and network biology to provide a direction for the development of novel drugs and therapies in curing the disease.
Application of Random Matrix Theory to Complex Networks
Spectral rigidity of spectra provides measure of randomness in underlying networks and potential of RMT framework is provided and obtained to understand and predict behavior of complex systems with underlying network structure.
Mapping drug-target interactions and synergy in multi-molecular therapeutics for pressure-overload cardiac hypertrophy
- A. Rai, Vikas Kumar, Gaurav Jerath, C. Kartha, Vibin Ramakrishnan
- BiologyNPJ systems biology and applications
- 15 February 2021
A chimeric approach involving in-vivo assays, gene expression analysis, cheminformatics, and network biology is employed to deduce the regulatory actions of a multi-constituent Ayurvedic concoction, Amalaki Rasayana, in animal models for its effect in pressure-overload cardiac hypertrophy.