Description#
The DNA sequence is composed of a series of nucleotides abbreviated as 'A'
, 'C'
, 'G'
, and 'T'
.
- For example,
"ACGAATTCCG"
is a DNA sequence.
When studying DNA, it is useful to identify repeated sequences within the DNA.
Given a string s
that represents a DNA sequence, return all the 10
-letter-long sequences (substrings) that occur more than once in a DNA molecule. You may return the answer in any order.
Example 1:
Input: s = "AAAAACCCCCAAAAACCCCCCAAAAAGGGTTT"
Output: ["AAAAACCCCC","CCCCCAAAAA"]
Example 2:
Input: s = "AAAAAAAAAAAAA"
Output: ["AAAAAAAAAA"]
Constraints:
1 <= s.length <= 105
s[i]
is either 'A'
, 'C'
, 'G'
, or 'T'
.
Solutions#
Solution 1: Hash Table#
We define a hash table $cnt$ to store the occurrence count of all substrings of length $10$.
We iterate through all substrings of length $10$ in the string $s$. For the current substring $t$, we update its count in the hash table. If the count of $t$ is $2$, we add it to the answer.
After the iteration, we return the answer array.
The time complexity is $O(n \times 10)$, and the space complexity is $O(n \times 10)$. Here, $n$ is the length of the string $s$.
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| class Solution:
def findRepeatedDnaSequences(self, s: str) -> List[str]:
cnt = Counter()
ans = []
for i in range(len(s) - 10 + 1):
t = s[i : i + 10]
cnt[t] += 1
if cnt[t] == 2:
ans.append(t)
return ans
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| class Solution {
public List<String> findRepeatedDnaSequences(String s) {
Map<String, Integer> cnt = new HashMap<>();
List<String> ans = new ArrayList<>();
for (int i = 0; i < s.length() - 10 + 1; ++i) {
String t = s.substring(i, i + 10);
if (cnt.merge(t, 1, Integer::sum) == 2) {
ans.add(t);
}
}
return ans;
}
}
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| class Solution {
public:
vector<string> findRepeatedDnaSequences(string s) {
unordered_map<string, int> cnt;
vector<string> ans;
for (int i = 0, n = s.size() - 10 + 1; i < n; ++i) {
auto t = s.substr(i, 10);
if (++cnt[t] == 2) {
ans.emplace_back(t);
}
}
return ans;
}
};
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| func findRepeatedDnaSequences(s string) (ans []string) {
cnt := map[string]int{}
for i := 0; i < len(s)-10+1; i++ {
t := s[i : i+10]
cnt[t]++
if cnt[t] == 2 {
ans = append(ans, t)
}
}
return
}
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| function findRepeatedDnaSequences(s: string): string[] {
const n = s.length;
const cnt: Map<string, number> = new Map();
const ans: string[] = [];
for (let i = 0; i <= n - 10; ++i) {
const t = s.slice(i, i + 10);
cnt.set(t, (cnt.get(t) ?? 0) + 1);
if (cnt.get(t) === 2) {
ans.push(t);
}
}
return ans;
}
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| use std::collections::HashMap;
impl Solution {
pub fn find_repeated_dna_sequences(s: String) -> Vec<String> {
if s.len() < 10 {
return vec![];
}
let mut cnt = HashMap::new();
let mut ans = Vec::new();
for i in 0..s.len() - 9 {
let t = &s[i..i + 10];
let count = cnt.entry(t).or_insert(0);
*count += 1;
if *count == 2 {
ans.push(t.to_string());
}
}
ans
}
}
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| /**
* @param {string} s
* @return {string[]}
*/
var findRepeatedDnaSequences = function (s) {
const cnt = new Map();
const ans = [];
for (let i = 0; i < s.length - 10 + 1; ++i) {
const t = s.slice(i, i + 10);
cnt.set(t, (cnt.get(t) || 0) + 1);
if (cnt.get(t) === 2) {
ans.push(t);
}
}
return ans;
};
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| public class Solution {
public IList<string> FindRepeatedDnaSequences(string s) {
var cnt = new Dictionary<string, int>();
var ans = new List<string>();
for (int i = 0; i < s.Length - 10 + 1; ++i) {
var t = s.Substring(i, 10);
if (!cnt.ContainsKey(t)) {
cnt[t] = 0;
}
if (++cnt[t] == 2) {
ans.Add(t);
}
}
return ans;
}
}
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Solution 2: Rabin-Karp String Matching Algorithm#
This method essentially combines sliding window and hash. Similar to 0028. Find the Index of the First Occurrence in a String, this problem can use a hash function to reduce the time complexity of counting subsequences to $O(1)$.
The time complexity is $O(n)$, and the space complexity is $O(n)$. Here, $n$ is the length of the string $s$.
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| func findRepeatedDnaSequences(s string) []string {
hashCode := map[byte]int{'A': 0, 'C': 1, 'G': 2, 'T': 3}
ans, cnt, left, right := []string{}, map[int]int{}, 0, 0
sha, multi := 0, int(math.Pow(4, 9))
for ; right < len(s); right++ {
sha = sha*4 + hashCode[s[right]]
if right-left+1 < 10 {
continue
}
cnt[sha]++
if cnt[sha] == 2 {
ans = append(ans, s[left:right+1])
}
sha, left = sha-multi*hashCode[s[left]], left+1
}
return ans
}
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