Open Source ChromeOS Data Labeling Tools

MANTI is a one-stop shop N-termini annotation & evaluation solution. MANTI was previously (un)known as muda.pl ahead of v3.7, the project was renamed to MANTI.pl with v3.7 on 2019-06-24. It congregates information from different MaxQuant or DiaNN/MSFragger output files into a master file suitable explicitly for protein neo-termini analyses. The central anchor for the data congregation is the modificationSpecificPeptides.txt or diann-output.pr_matrix.tsv file - additional data is inferred from different other source files from the corresponding folder. Maybe also useful for normal proteomics purposes but this script is heavily optimized for protein neo-termini identification and validation. A graphical interface is available as Yoğurtlu_MANTI (a Perl/Tk script) + execut. application versions for Win1x without the need to have Perl installed locally. For a very detailed explanation of script parameters and the evaluation strategy, please consult the extensive manual PDF

-------- ATTENTION START: RENAMING muda.pl was renamed to MANTI.pl with v3.7, project development can be tracked on the MANTI project page on sourceforge.net. Old versions remain here for archival purposes. -------- ATTENTION END muda.pl is an evaluation script (written in Perl) without great dependencies. It congregates information from 4 different MaxQuant output files into a master file suitable explicitly for protein neo-termini analyses. The central anchor for the data congregation is the modificationSpecificPeptides.txt file - additional data is inferred from different other source files from the MaxQuant txt folder but the starting point for the data assembly is solely the modificationSpecificPeptides.txt file. Maybe also useful for normal proteomics purposes but this script is heavily optimized for protein neo-termini identification and validation. For a more thorough explanation of script parameters and evaluation strategy, please consult the extensive manual PDF.

This project helps to digitize field data for a certain Bird Census method. Namely, bird census based on personal inspection or small (~10 km^2) regions with recording birds' position and behaviour on paper. This project makes it easy to annotate such field data and to make this data available for statistical analysis.

H9A is an installable Python package that counts how many times a given digit appears in a range of numbers (by default: the digit 9 between 1 and 100). It provides both a h9a command-line tool and an importable library, and it prints each step of the calculation — the per-place counts and the combined total — as styled, colorized output. It is built with rich for console formatting, pyfiglet for an ASCII-art banner, and Pillow for optional terminal-style screenshots.