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πŸ“€
HPCing
πŸ“€
HPCing

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@HCEMM

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iquasere/README.md

Hi there! πŸ‘‹

I was a PhD student, using bioinformatics to "Uncover the role of conductive nanomaterials in anaerobic digestion".

Tools for meta-omics analyses

My work has mostly been the development of tools for analyses of meta-omics data, i.e., the study of the collective genomes, transcriptomes or proteomes of a microbial community.

These are the main tools I have developed for meta-omics analyses:

UPIMAPI, reCOGnizer and KEGGCharter

UPIMAPI, reCOGnizer and KEGGCharter are tools developed for the analyses of omics data, and optimized for handling the challenges of meta-omics.

MOSCA

MOSCA is a powerful pipeline developed for metagenomics (MG), metatranscriptomics (MT) and metaproteomics (MP) integrated analyses.

Finally, some metrics about my coding routine:

Code Time

AI Code Time

I'm an Early 🐀

🌞 Morning                1773 commits        β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   23.48 % 
πŸŒ† Daytime                3959 commits        β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   52.43 % 
πŸŒƒ Evening                1428 commits        β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   18.91 % 
πŸŒ™ Night                  391 commits         β–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   05.18 % 

πŸ“… I'm Most Productive on Wednesday

Monday                   1331 commits        β–ˆβ–ˆβ–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   17.63 % 
Tuesday                  1728 commits        β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   22.88 % 
Wednesday                1894 commits        β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   25.08 % 
Thursday                 1071 commits        β–ˆβ–ˆβ–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   14.18 % 
Friday                   1006 commits        β–ˆβ–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   13.32 % 
Saturday                 57 commits          β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   00.75 % 
Sunday                   464 commits         β–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   06.14 % 

πŸ“Š This Week I Spent My Time On

πŸ’¬ Programming Languages: 
YAML                     5 hrs 24 mins       β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‘β–‘β–‘   88.10 % 
Other                    23 mins             β–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   06.35 % 
Markdown                 12 mins             β–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   03.45 % 
HTML                     2 mins              β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   00.76 % 
Python                   2 mins              β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   00.62 % 

πŸ±β€πŸ’» Projects: 
ansible-puli             5 hrs 42 mins       β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‘β–‘   92.89 % 
my6                      22 mins             β–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   06.09 % 
Unknown Project          2 mins              β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   00.76 % 
let                      0 secs              β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   00.26 % 

πŸ€– AI Coding This Week

⏱ AI Coding Time: 23 mins (6.35%)

✍️ 0 lines written by AI, 324 lines written by hand (0.0% AI-written)

πŸ”€ 150,262 Input Tokens, 18,677 Output Tokens

πŸ’΅ $8.94 Estimated AI Cost This Week

🧠 2 AI Sessions, 4 AI Prompts

GPT                      0 lines             β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   00.00 % 

πŸ”Ž AI Coding Insights:
πŸ§‘β€πŸ’» Mostly Hands-On β€” 0.0% of written lines came from AI
πŸ“„ Detailed Prompter β€” average 1,033 characters per prompt
πŸ” Iterative Prompter β€” average 2 prompts per session
πŸ” Hands-On Reviewer β€” 100.0% of changed lines were hand-edited

I Mostly Code in Python

Python                   11 repos            β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   32.35 % 
HTML                     10 repos            β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   29.41 % 
Java                     4 repos             β–ˆβ–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   11.76 % 
Shell                    2 repos             β–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   05.88 % 
JavaScript               1 repo              β–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘   02.94 % 

Last Updated on 24/10/2026 21:15:44 UTC

Pinned Loading

  1. reCOGnizer reCOGnizer Public

    A tool for domain based annotation with databases from the Conserved Domains Database

    HTML 29 3

  2. UPIMAPI UPIMAPI Public

    UniProt Id Mapping through API

    Python 39 5

  3. KEGGCharter KEGGCharter Public

    A tool for representing genomic potential and transcriptomic expression into KEGG pathways

    Python 63 8

  4. MOSCA MOSCA Public

    Meta-Omics Software for Community Analysis

    Python 36 7

  5. annotation_paper annotation_paper Public

    UPIMAPI, reCOGnizer and KEGGCharter: bioinformatics tools for fast functional annotation and visualization of (meta)-omics datasets

    Python 4

  6. MOSGUITO MOSGUITO Public

    MOSca's GUI TO perform meta-omics analyses

    HTML 2 2