TSMDA is a machine learning-based model that leverages target and symptom information and two robust negative sample selection approaches to accurately predict potential miRNA-disease associations. This model was created based on available known associations in HMDD v2.0.
(A) represents the main page of TSMDA:
If you are contacting us regarding a job submission, please include its details such as input information and the job identifier.
(B) depicts the submission page:
(C) represents the waiting step:
(D) presents the result page for TSMDA.