BionetBF: A Novel Bloom Filter for Faster Membership Identification of Large Biological Graph

Generate Dataset

To generate dataset, first compile

• $gcc data-gen-id_Kmer.c

and then run the code

• $./a.out

Compiling and running main code

To compile the main code

• $gcc BionetBF.c

To run the code

• $./a.out

Citation:

• Nayak, Sabuzima and Patgiri, Ripon, Bionetbf: A Novel Bloom Filter for Faster Membership Identification of Large Biological Graph. Available at SSRN: https://ssrn.com/abstract=4170144 or http://dx.doi.org/10.2139/ssrn.4170144

@misc{nayak_bionetbf:_2022,
	address = {Rochester, NY},  
	type = {{SSRN} {Scholarly} {Paper}},  
	title = {Bionetbf: {A} {Novel} {Bloom} {Filter} for {Faster} {Membership} {Identification} of {Large} {Biological} {Graph}},  
	shorttitle = {Bionetbf},
	url = {https://papers.ssrn.com/abstract=4170144},
	doi = {10.2139/ssrn.4170144},
	urldate = {2022-10-11},
	author = {Nayak, Sabuzima and Patgiri, Ripon},
	month = jul,
	year = {2022},
	keywords = {Keywords: Bloom Filter, Big Graph, Biological Network, Probabilistic Data Structure, algorithm},
}

Contributed by

• Ms. Sabuzima Nayak

• Dr. Ripon Patgiri, URL: http://cs.nits.ac.in/rp