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q-bio.NC · Neurons and Cognitionq-bio.QM · Quantitative Methods

Fourteen source profiles gave the full rank of 91 in a fixed linear model of three 2024 C. elegans peptide maps

We tested which peptide channel gains can be distinguished from complete neuron pair coefficients in a fixed linear model. We used 92 binary channel layers from the 2 February 2024 C. elegans release. Each gain was a single scalar shared by all neuron pairs. The full design had rank 91 in the short-range, mid-range and long-range maps. The NLP-2–GNRR-6 and NLP-23–GNRR-6 columns were equal. Their sum was identifiable, but their difference was not. All other 90 gains were identifiable under the model. The same 14-source panel retained rank 91 in all three maps. An exact integer certificate proved that no panel of 13 sources can do so. The proof used requirements with total weight 27 and a maximum weight of two per source. Self-pair inclusion did not change these results. One ideal direct coefficient after a fixed nlp-2 deletion raised the baseline design rank to 92. These are algebraic results for known binary layers and exact direct coefficients. They do not establish a sufficient physiological experiment or measured peptide strengths. The package preserves code, aligned data, source hashes, figures, exact certificates and repeat instructions.

C. elegans · neuropeptide connectome · identifiability · matrix rank · source selection · experimental design · exact certificate

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References

6
  1. usesdoi:10.1016/j.neuron.2023.09.043

    We use the 2024 release of the 92 peptide channel maps from this study. The supporting manifest pins each source file.

  2. usesdoi:10.6084/m9.figshare.c.6895870.v1

    This source collection gives the primary data record. The tested bytes are fixed by the later Git commit and source checksums.

  3. doi:10.1016/j.cell.2021.06.023

    This expression resource supports the source layers. It already reports restricted nlp-2 and nlp-23 expression in AWA.

  4. doi:10.1016/j.celrep.2023.113058

    This study supplies biochemical context for the peptide and receptor matches in the maps.

  5. doi:10.1085/jgp.201611702

    This study gives prior work on parameter identifiability in receptor models.

  6. usesOne gene loss removes all listed support for 5,407 multichannel connections in the 2024 short-range C. elegans peptide model sci:sha256:ca108f7e42c2e47e88eeb5d6ad7b4aaa0d7a256d19e214b2bc1d3ef954ae4367

    We use its source provenance to locate the verified shared cache. It tested gene loss in the same channel layers. Our code and rank tests are new.

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