Network controllability solutions for computational drug repurposing using genetic algorithms

Control theory has seen recently impactful applications in network science, especially in connections with applications in network medicine. A key topic of research is that of finding minimal external interventions that offer control over the dynamics of a given network, a problem known as network controllability. We propose in this article a new solution for this problem based on genetic algorithms. We tailor our solution for applications in computational drug repurposing, seeking to maximize its use of FDA-approved drug targets in a given disease-specific protein-protein interaction network. We demonstrate our algorithm on several cancer networks and on several random networks with their edges distributed according to the Erdos-Renyi, the Scale-Free, and the Small World properties. Overall, we show that our new algorithm is more efficient in identifying relevant drug targets in a disease network, advancing the computational solutions needed for new therapeutic and drug repurposing approaches

STREAM AUTHENTICATION BASED ON GENERLIZED BUTTERFLY GRAPH

ABSTRACT This paper proposes a stream authentication method based on the Generalized Butterfly Graph (GBG) framework. Compared with the original Butterfly graph, the proposed GBG graph supports an arbitrary overhead budget and number of packets. Within the GBG framework, the problem of constructing an authentication graph is considered as a design problem: Given total number of packets, packet loss rate, and overhead budget, we show how to design the graph (number of rows and columns and edge allocation among nodes) to maximize the expected number of verified packets. In addition, we also propose a new evaluation metric called Loss-Amplification-Factor (LAF), which measures the extent to which the authentication method exacerbates the effective packet loss rate. Experimental results demonstrate significant performance improvements over existing authentication methods like EMSS, Augmented Chain, and the original Butterfly

Optimized protection of streaming media authenticity

Ph.DDOCTOR OF PHILOSOPH