Diper: detection and identification of pathogens using edit distance-tolerant resistive cam

HIGHLIGHTS

• What: - the authors propose a novel resistive edit distance-tolerant content addressable memory for computational genomics applications particularly for detection and identification of pathogens of pandemic importance. To alleviate this fundamental limitation, the authors propose a resistive edit distance-tolerant content addressable memory (DIPER), which is capable of tolerating a user-configurable edit (rather than Hamming) distance. The authors present a fast, highly sensitive and precise approximate matching-based DNA detection and identification solution, implemented by DIPER. To evaluate the impact of global and local variations on DIPER classification efficiency, the authors focus on the most challenging . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or Email

  Password

  Remember me

  Lost your password?

  If you don't have an account, you can create one here.