🚀 Winner of the Donnelly Centre Innovation and Commercialization award: Apply diffusion models to deconvolute highly multiplexed DIA-MS/MS data by conditioning on MS1 signals to generate cleaner MS2 data for downstream analysis.
active 2024-10-07 → 2025-04-10 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 186 days from 2024-10-07 to 2025-04-10. Pushes: 114 total, peak 10 in a day. Pull requests: 25 total, peak 2 in a day. Issues: 15 total, peak 5 in a day. Comments: 170 total, peak 17 in a day. Stars: 7 total, peak 1 in a day.
- Pushes
- Pull requests
- Issues
- Comments
- Stars
Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| singjc | 162 | 73 | 14 | 59 |
| dev-coder2 | 74 | 0 | 4 | 50 |
| CoderOMaster | 53 | 0 | 3 | 46 |
| LLYX | 38 | 38 | 0 | 0 |
| nithin200417 | 9 | 0 | 1 | 5 |
| s7d1 | 3 | 3 | 0 | 0 |
| bhautik-pithadiya | 3 | 0 | 0 | 3 |
| Dragonwagon18 | 2 | 0 | 2 | 0 |
| mandeepnh5 | 2 | 0 | 0 | 2 |
| jeeth-kataria | 1 | 0 | 1 | 0 |
| SupriyaKamatagi | 1 | 0 | 0 | 1 |
| sharon-kathambi | 1 | 0 | 0 | 1 |
| Omar-Ayman10 | 1 | 0 | 0 | 1 |
| vdemichev | 1 | 0 | 0 | 1 |
| ShubhamChauhan22222 | 1 | 0 | 0 | 1 |
Recent activity
Latest issues, pull requests and releases
- Issue comment#36dev-coder22025-04-10 09:31Add Feature_extraction.py for Batch & Parallel MS1/MS2 Feature Extraction
- Issue comment#20dev-coder22025-04-05 17:40[GSoC 2025] Generate MS1 and MS2 Peptide Feature Masks for Targeted Deconvolution
- Issue comment#20CoderOMaster2025-04-05 17:37[GSoC 2025] Generate MS1 and MS2 Peptide Feature Masks for Targeted Deconvolution
- Issue comment#20dev-coder22025-04-05 16:26[GSoC 2025] Generate MS1 and MS2 Peptide Feature Masks for Targeted Deconvolution
- Issue comment#20CoderOMaster2025-04-05 16:08[GSoC 2025] Generate MS1 and MS2 Peptide Feature Masks for Targeted Deconvolution
- Issue comment#36dev-coder22025-04-05 15:43Add Feature_extraction.py for Batch & Parallel MS1/MS2 Feature Extraction
- Issue comment#36singjc2025-04-04 17:08Add Feature_extraction.py for Batch & Parallel MS1/MS2 Feature Extraction
- Issue comment#36dev-coder22025-04-04 17:04Add Feature_extraction.py for Batch & Parallel MS1/MS2 Feature Extraction
- Pull request#30singjc2025-04-04 14:19
- Issue comment#30singjc2025-04-04 14:19Quantization(Dynamic and static)
- Issue comment#31dev-coder22025-04-01 17:04Add precursor_cond support in diffusion model for precursor feature masks integration
- Pull request#35dev-coder22025-03-31 07:50
- Issue comment#20dev-coder22025-03-31 07:28[GSoC 2025] Generate MS1 and MS2 Peptide Feature Masks for Targeted Deconvolution
- Pull request#35dev-coder22025-03-31 07:25
- Issue comment#30CoderOMaster2025-03-30 18:08Quantization(Dynamic and static)
- Issue comment#16SupriyaKamatagi2025-03-30 13:36[GSoC 2025] Optimize Data Generation Pipeline for DIA-MS Diffusion Model
- Issue comment#20dev-coder22025-03-28 18:27[GSoC 2025] Generate MS1 and MS2 Peptide Feature Masks for Targeted Deconvolution
- Pull request#34singjc2025-03-28 18:17
- Issue comment#34singjc2025-03-28 18:17Add Notebook for DIA-NN Output Conversion and MS1/MS2 Feature Extraction via MassDASH
- Issue comment#34dev-coder22025-03-28 18:11Add Notebook for DIA-NN Output Conversion and MS1/MS2 Feature Extraction via MassDASH
- Issue comment#34singjc2025-03-28 17:51Add Notebook for DIA-NN Output Conversion and MS1/MS2 Feature Extraction via MassDASH
- Issue comment#34singjc2025-03-28 14:46Add Notebook for DIA-NN Output Conversion and MS1/MS2 Feature Extraction via MassDASH
- Issue comment#30singjc2025-03-28 14:29Quantization(Dynamic and static)
- Issue comment#34dev-coder22025-03-25 19:30Add Notebook for DIA-NN Output Conversion and MS1/MS2 Feature Extraction via MassDASH
- Issue comment#30CoderOMaster2025-03-25 15:06Quantization(Dynamic and static)
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 7 stars here means stars gained during the window, not the repo's star count.