id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-287634-64zqe4cz	Al-Ssulami, Abdulrakeeb M.	CodSeqGen: A tool for generating synonymous coding sequences with desired GC-contents	2020-01-31		.txt	text/plain	2307	137	59	For generating synthetic coding sequences with pre-specified amino acid sequence and desired GC-content, there exist two stochastic methods, multinomial and maximum entropy. In this paper, we present an algorithmic solution to produce coding sequences that follow exactly a primary amino acid sequence and a desired GC-content. Thus, identifying over/under-represented regulatory elements or genome-scale patterns relies on generating random sequences that obey the pre-specified amino acid sequence and GC-content constraints. A more restricted method was presented recently, which the authors named NullSeq. NullSeq [10] uses the maximum entropy approach where the synonymous codon usage probability is derived from a strict function that expresses the expected GC-content in the reference amino acid sequence. We ran both tools, CodSeqGen and NullSeq [10] , to generate 1000 coding sequences given the primary amino acid sequence and the target GC-content of the reference coding sequence. NullSeq: a tool for generating random coding sequences with desired amino acid and GC contents	./cache/cord-287634-64zqe4cz.txt	./txt/cord-287634-64zqe4cz.txt