# UCL CoMPLEX MRes module — Data

来源：https://www.kaggle.com/competitions/UCL/data

采集时间：2026-10-20T03:16:05Z

These sequences are from patients who had only recently contracted HIV-1 and had not been treated before.
The Dataset is organized as follows:
Col-1: patient ID
Col-2: responder status ("1" for patients who improved and "0" otherwise)
Col-3: Protease nucleotide sequence (if available)
Col-4: Reverse Transciptase nucleotide sequence (if available)
Col-5: viral load at the beginning of therapy  (log-10 units)
Col-6: CD4 count at the beginning of therapy
The
 Responder status indicates whether the patient improved after 16 weeks 
of therapy.  Improvement is defined as a 100-fold decrease in the HIV-1 
viral load.
There's a brief description of 
Protease nucleotide sequence, Reverse Transciptase nucleotide sequence, 
viral load and CD4 count on the background page.
training_data.csv is the training dataset used to calibrate your model.
test_data.csv is the test datset used to generate submissions.
Your submission must contain predictions for 692 patients.
Submissions must be in CSV format. template.csv is a submission template. You are expected to fill your predicted responder status in column 2. A responder status of 1 indicates that a patient has improved; or 0 otherwise. example.csv is an example submission.