Abstract: Engineered FnCas9 variants are provided that have an enhanced kinetic activity and a broader PAM recognition. The protein engineering methodology introduced specific mutations that stabilized interaction between Cas9 enzyme and target DNA. The enhanced kinetic activity increases NHEJ-mediated editing, owing to more efficient DSB generation potential than WT FnCas9, and the broadened PAM specificity increases the target range of FnCas9 variants. Thus, the scope and accessibility of CRISPR-Cas9 system targets are widened, along with generating robust and highly specific engineered FnCas9 variants.

Abstract: Method and system for narrow passage path sampling based on levy flight is disclosed. The disclosed technique is an improvisation of Random Walk to Surface (RWS), wherein, instead of performing a random walk, the disclosed technique utilizes levy flight mechanism to identify samples in narrow passages (on the obstacle boundaries). The disclosed technique for identification of narrow passages sampling points in the narrow passage is based on several techniques that include random uniform sampling technique, a levy flight function (step size) and a collision detection technique. Moreover, in addition to identification of narrow passages sampling points, the disclosed technique also performs an additional check to ensure that the identified narrow passages sampling points are present in the narrow passage based on a levy flight bridge sampler technique.

Abstract: An auction-based bid generation technique is a NP-hard problem and is not suitable for real-time scheduling of multi-agents. The embodiments thus provide a system and method for scheduling a set of tasks among a plurality of agents. Herein, agents self-allocate tasks among themselves dynamically in a distributed fashion, following an ordered sequence of agent indexes. The motivation of following the ordered sequence of agent indexes is allowing each agent to select its best strategy once by exploiting the greedy characteristic of the agent. The preferred agent (based on the ordered sequence) self-allocates tasks among multiple based on the minimum L2 Norm between task attributes and agent attributes, results in a strategy. The strategy offered by a sequence needs to satisfy constraints. A heuristic reward function for each strategy is proposed. Based on these rewards, agents reach consensus by playing an exact potential game for scheduling tasks among the agents.