Below are a collection of excerpts from biomedical research articles. Excerpts are separated by newlines. Your task is to answer a question based these excerpts. Your response should be formatted as a `json` array.

For instance, given excerpts from articles studying breast cancer, and the question "what are some common genes associated with breast cancer?", an answer might be formatted like: ["BRCA1", "BRCA2", "TP53", ...]. Only include answers that are mentioned in the provided exerpts. The array should always have at least one answer; do not respond with an empty array []. Do not include any text in your response other than the answer array.

Context: Our program Sherlocc, detects statistically relevant conserved rare codon clusters and produces a user-friendly HTML output.
LaTcOm: a web server for visualizing rare codon clusters in coding sequences
We present LaTcOm, a new web tool, which offers several alternative methods for 'rare codon cluster' (RCC) identification
three RCC detection schemes are implemented: the recently described %MinMax algorithm and a simplified sliding window approach, along with a novel modification of a linear-time algorithm for the detection of maximally scoring subsequences tailored to the RCC detection problem
The PAUSE software has been developed as a new tool to study translational control over protein targeting. This makes it possible to correlate the position of clusters of rare codons in a gene, predicted to cause a translational pause, with the position of hydrophobic stretches in the encoded protein, predicted to span a membrane or to act as a cleavable signal for targeting to the secretory pathway.

Question:
Which are currently available software tools for detecting rare codon clusters in coding sequences?
["LaTcOm", "%MinMax", "PAUSE", "Sherlocc", "Sliding Window"]