map map f [x, y, z] = [f x, f y, f z] fmap_List :: (a -> b) -> [] a -> [] b — “[] a” means “[a]” in types. fmap_List f [] = [] fmap_List f (x:xs) = f x : fmap_List f xs Maybe data Maybe a = Nothing | Just a […]
程序代写代做代考 DNA C flex map map f [x, y, z] = [f x, f y, f z] Read More »
diffSq :: Integer -> Integer -> Integer diffSq x y = (x – y) * (x + y) diffSq 2 1 X -> Y -> Z diffSqV3a, diffSqV3b :: Integer -> Integer -> Integer diffSqV3a x y = let minus = x – y plus = x + y in minus * plus diffSqV3b x
程序代写代做代考 DNA go diffSq :: Integer -> Integer -> Integer Read More »
\ lambda x : x+1 function (x) { return x+1; } x => x+1 \x -> x+1 (\y -> 2*x – 3*y) \x y -> 2*x – 3*y diffSq x y = (x – y) * (x + y) diffSq = \x y -> (x – y) * (x + y) diffSq x = \y
mySumV1 [] = 0 mySumV1 (x:xt) = x + mySumV1 xt myProductV1 [] = 1 myProductV1 (x:xt) = x * myProductV1 xt — This function is also in the standard library, under the name “map”. — We write it again to make a bigger point. — E.g., myMap f [1, 2, 3] = [f 1,
程序代写代做代考 DNA mySumV1 [] = 0 Read More »
(==) :: Integer -> Integer -> Bool (==) :: Char -> Char -> Bool (==) :: Bool -> Bool -> Bool — Similarly for (/=) the not-equal operator. class ClassName typeVar where methodName :: type sig containing typeVar — Optional: default implementations == /= Eq class Eq a where (==), (/=) :: a -> a
程序代写代做代考 DNA algorithm Haskell (==) :: Integer -> Integer -> Bool Read More »
foo bar f (3+4, div(4, 2)) f (7, div(4, 2)) f (7, 2) 7 f (3+4, div(1, 0)) f (7, div(1, 0)) ☹ take 3 [a,b,c,d,e] = [a,b,c] take 3 [a,b] = [a,b] take 0 _ = [] take _ [] = [] take n (x:xs) = x : take (n-1) xs doITerminate = take
程序代写代做代考 DNA C foo bar Read More »
CS 369 2020 Assignment 4 Due Wednesday June 10 10:00 pm In the first part of this assignment, we use a Hidden Markov Model to model secondary structure in protein sequences and implement a couple of algorithms we saw in lectures. In the second part, we simulate sequences down a tree according to the Jukes-Cantor
程序代写代做 Hidden Markov Mode html Bayesian DNA algorithm CS 369 2020 Assignment 4 Read More »
CS 369 2020 Assignment 4 Due Wednesday June 10 10:00 pm In the first part of this assignment, we use a Hidden Markov Model to model secondary structure in protein sequences and implement a couple of algorithms we saw in lectures. In the second part, we simulate sequences down a tree according to the Jukes-Cantor
程序代写代做 Hidden Markov Mode html Bayesian DNA algorithm CS 369 2020 Assignment 4 Read More »
✏ X ⌧ B 12⌧ M ⌧ E 1 2 ⌧ ✏ ⌧ ⌧ Y Figure 8: A pair HMM model for global alignment. Emission probabilities for states M, X, Y are pxiyj , qxi and qyj , respectively. Compare it to the simpler FSA in Figure 2. 10 Applications of HMMs in bioinformatics 10.1
程序代写代做 Hidden Markov Mode html algorithm C Bioinformatics DNA ✏ Read More »
CS 369 2020 Assignment 4 Due Wednesday June 10 10:00 pm In the first part of this assignment, we use a Hidden Markov Model to model secondary structure in protein sequences and implement a couple of algorithms we saw in lectures. In the second part, we simulate sequences down a tree according to the Jukes-Cantor
程序代写代做 DNA Bayesian Hidden Markov Mode algorithm html CS 369 2020 Assignment 4 Read More »