Abdulkadir Çelikkanat, Andres Masegosa, Thomas Nielsen
We lifted 4 functions out of this paper's own repositories and ran 3 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.
| Repository | Role | Ran |
|---|---|---|
| abdcelikkanat/revisitingkmers | canonical | 3 of 4 |
| Function | Status | Where it lives |
|---|---|---|
| NonLinearModel | Ran | abdcelikkanat/revisitingkmers/src/nonlinear.py pointer only (licence: NONE) · get_code("c55d239688ccb919") |
| loss_func | Ran | abdcelikkanat/revisitingkmers/src/nonlinear.py pointer only (licence: NONE) · get_code("b8415a5ca4e28ff0") |
| single_epoch | Ran | abdcelikkanat/revisitingkmers/src/nonlinear.py pointer only (licence: NONE) · get_code("fdf60a19696b351b") |
| set_seed | Not yet run | abdcelikkanat/revisitingkmers/src/nonlinear.py pointer only (licence: NONE) · get_code("6ac11eed8defa8ca") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
Obtaining effective representations of DNA sequences is crucial for genome analysis. Metagenomic binning, for instance, relies on genome representations to cluster complex mixtures of DNA fragments from biological samples with the aim of determining their microbial compositions. In this paper, we revisit k-mer-based representations of genomes and provide a theoretical analysis of their use in representation learning. Based on the analysis, we propose a lightweight and scalable model for performing metagenomic binning at the genome read level, relying only on the k-mer compositions of the DNA fragments. We compare the model to recent genome foundation models and demonstrate that while the models are comparable in performance, the proposed model is significantly more effective in terms of scalability, a crucial aspect for performing metagenomic binning of real-world datasets.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2411.02125")
get_code_for_paper("2411.02125")
have("2411.02125")
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