forecast
Peptides
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forecast
- Repost - R Package for Creating Linear Forecasting Models
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Ask HN: Data Scientists, what libraries do you use for timeseries forecasting?
As a few other people have mentioned, I find R to be the easiest tool for this job, specifically the forecast package [0]. I had to use this package for an applied econometrics course in college a few years ago, and I have been using it ever since. I find the syntax to be more straightforward than comparable libraries in Python. I also assume that this library (and other libraries in R) offer higher quality models and results than their counterparts in Python, but this is just an assumption.
[0] https://github.com/robjhyndman/forecast
Peptides
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Looking for a program that computes the hydrophobicity of a peptide
As others have there's Biopython. In R the Alakazam package has a function for computing GRAVY and there's also the peptides package.
What are some alternatives?
parsel - parallel execution of RSelenium
nflfastR - A Set of Functions to Efficiently Scrape NFL Play by Play Data
lmForc - R package for evaluating linear forecasting models.
worldfootballR - A wrapper for extracting world football (soccer) data from FBref, Transfermark, Understat and fotmob
modeltime.ensemble - Time Series Ensemble Forecasting
future - :rocket: R package: future: Unified Parallel and Distributed Processing in R for Everyone
rtypeform - An R interface to the 'typeform' API.
hydrophobic_moment - Script to calculate hydrophobic moment and other basic properties from protein sequences
HoRM - Supplemental Functions and Datasets for "Handbook of Regression Methods"
seurat - R toolkit for single cell genomics
tsfel - An intuitive library to extract features from time series.
darts - A python library for user-friendly forecasting and anomaly detection on time series.