Published September 25, 2024
| Version v1
Dataset
Open
Impact of Interval Censoring on Data Accuracy and Machine Learning Performance in Biological High-Throughput Screening
Authors/Creators
Description
Overview
Data and Results used in the publication entitled "Impact of Interval Censoring on Data Accuracy and Machine Learning Performance in Biological High-Throughput Screening"
Data
This folder contains the raw data used during this work.
`EvoEF.csv` contains information on the library used (sequences, number of mutations, etc.) and the fitness (energy) used as continuous mean values. `mut.csv` contains the information about the combinatorial scaling (N vs N_norm), the number of mutations (m) and the probability of each variant using different distributions (uniform and binomial) at different $p_{WT}$.
For further details on how the fitness values were calculated and how the combinatorial scale works, please refer to our prevoius [Paper](https://arxiv.org/abs/2405.05167).
Results
This folder contains the results (outputs) of all scripts used. Such results are included in the form of `.npy` and `.npz` files. To load such files with numpy you should include the option `allow_pickle=True`.
Files
HMLC.zip
Files
(108.3 MB)
| Name | Size | Download all |
|---|---|---|
|
md5:05e1aa6a50e3d704f25a5811b53d0128
|
108.3 MB | Preview Download |
Additional details
Software
- Repository URL
- https://github.com/Nash-Lab/HMLC
- Programming language
- Python