---
language:
  - en
tags:
  - biology
  - biophysics
  - proteomics
  - thermodynamics
  - drug-discovery
  - zero-shot
  - protein-structure
  - computational-biology
  - genomics
  - phenomics
  - crispr
  - cell-biology
  - drug-target
  - landauer
  - information-theory
  - quantum biology
  - digital biology
  - transcriptomics
  - cheminformatics
  - bioinformatics


pretty_name: Infoton Identity — 735 Human Proteins
size_categories:
  - 1K<n<10K
task_categories:
  - feature-extraction
  - other

---

# An Infoton Dose of RxRx — 735 Human Proteins

**Version:** 1.0.0
**Released:** 2026-09-06
**Author:** Walker, January Natatia — Infoton
**DOI:** [10.5281/zenodo.18210355](https://doi.org/10.5281/zenodo.18210355)
**ORCID:** [0009-0000-6843-2051](https://orcid.org/0009-0000-6843-2051)

---

## Overview

The Infoton Identity Physics Engine computes in seconds per protein and aligns with what cellular imaging measures. The coordinates in the An Infoton Dose of RxRx dataset were derived before correlation was run with timestamp proof.

An Infoton Dose of RxRx provides Infoton thermal coordinates for 735 human proteins selected from a publicly available cellular imaging benchmark gene set, computed from first principles using AME2020 nuclear mass tables and the Infoton equation:

```
m(T) = kBT ln(|P⟩) / c²

```

derived from Landauer's principle and Marić-Einstein's mass-energy equivalence.
kB is the Boltzmann constant, T is temperature in Kelvin, c is the speed of light (CODATA 2018).

**Zero free parameters. Zero training. Zero experimental inputs.**

Coordinates are determined entirely from:
- Protein sequences: UniProt Swiss-Prot (reviewed)
- Atomic masses: AME2020 nuclear mass table
- Physical constants: CODATA 2018
- Infoton: A Fundamental Particle of Information-Energy

---

## Key Result

The Infoton Identity, atomic thermal coordinates derived from first principles, aligns with experimentally measured CRISPR knockout phenotype severity across 735 proteins at Kendall tau = +0.111 (p = 0.0000068, N = 735, zero free parameters, zero training on imaging data). Sign was preserved on held-out set. Picard et al. (2015) anchors: 21/21.

With a p = 0.0000068 and N = 735 random proteins, a researcher would have to run the experiment 147,059 times before expecting to see the tau = +0.111 result by accident even once. The Infoton Physics Engine does not produce Identity results by accident. The Infoton Engine derives results from atomic masses. The p-value measures how clearly that derivation rises above experimental noise.

---

## Dataset Contents

### infoton_thermal_identities.parquet
Summary Infoton Thermal Identities. 735 rows, one per protein.

|| Column | Type | Description |
|--------|------|-------------|
| gene_symbol | str | HGNC gene symbol |
| uniprot_id | str | UniProt accession (reviewed) |
| protein_name | str | Full protein name |
| sequence_length_aa | int | Protein length in amino acids |
| logT_centroid | float | log10 Infoton temperature, mean over residues |
| logm_centroid | float | log10 Infoton mass, mean over residues |
| Cp_invariant | float | log10(T) minus log10(m); verified = 39.97273266 |
| Cp_verified | bool | Invariant within 1e-4 tolerance |
| Cp_violations | int | Residues outside tolerance |
| HIS_total | float | Harmonic information score, summed |
| HIS_per_aa | float | Harmonic information score per residue |
| FP_total_kcal | float | Frustration potential, summed (kcal/mol) |
| FP_per_aa | float | Frustration potential per residue (kcal/mol) |
| sub_harmonic_mean | float | Mean sub-harmonic coupling score |
| dominant_gap_mean | float | Mean dominant bond thermal gap (delta logT) |
| dominant_bond_type | str | Most frequent dominant bond type across residues |
| n_bonds_total | int | Total bonds enumerated |
| f_NH | float | N-H bond fraction |
| n_NH | int | N-H bond count |
| n_CH | int | C-H bond count |
| n_CO | int | C-O bond count |
| n_NC | int | N-C bond count |
| n_CC | int | C-C bond count |
| n_CS | int | C-S bond count |
| n_NO | int | N-O bond count |



### infoton_residue_profiles.parquet
 441,296 rows.

| Column | Type | Description |
|--------|------|-------------|
| gene_symbol | str | HGNC gene symbol |
| uniprot_id | str | UniProt accession |
| position | int | Residue position (1-indexed) |
| amino_acid | str | Single-letter code |
| amino_acid_name | str | Full amino acid name |
| context | str | N-terminal / C-terminal / internal |
| logT_centroid | float | log10 Infoton temperature |
| logm_centroid | float | log10 Infoton mass |
| HIS_residue | float | Harmonic information score |
| FP_kcal | float | Frustration potential (kcal/mol) |
| dominant_gap | float | Dominant bond thermal gap (delta logT) |
| dominant_bond_type | str | Bond type with largest thermal gap |
| sub_harmonic_score | float | Sub-harmonic coupling score |
| net_coupling_score | float | Net coupling score |
| delta_water_logT | float | Deviation from water reference (logT) |
| landauer_freq_Hz | float | Landauer frequency (Hz) |
| mass_u | float | Residue mass, atomic mass units (AME2020) |

---

## The Cp Invariant

Every residue in this dataset satisfies:

```
log10(T) - log10(m) = 39.97273266
```

derived from fundamental physical constants:

```
Cp = log10(c² / (kB · ln(2))) = 39.97273266
```

CODATA 2018. Verified across all Standard Model particles, all 118 elements, and all 441,296 residues in this release. Cp_violations = 0 throughout.

---

## Quick Start

```python
from huggingface_hub import hf_hub_download
import pandas as pd

path = hf_hub_download(
    "januarian-physics/an-infoton-dose-of-rxrx",
    filename="infoton_thermal_identities.parquet",
    repo_type="dataset"
)
df = pd.read_parquet(path)
print(df[['gene_symbol','uniprot_id','logT_centroid',
          'HIS_per_aa','f_NH','Cp_invariant']].head(10))

path2 = hf_hub_download(
    "Infoton/infoton-human-protein-identities",
    filename="infoton_residue_profiles.parquet",
    repo_type="dataset"
)
residues = pd.read_parquet(path2)

tp53 = residues[residues['gene_symbol'] == 'TP53'].copy()
print(f"TP53: {len(tp53)} residues")
print(tp53[['position','amino_acid','logT_centroid',
            'HIS_residue','sub_harmonic_score']].head())
```

---

## Validation

Infoton Identity thermal coordinates were tested against external experimental data prior to publication.

**Primary result:** Kendall tau = +0.111, p = 0.0000068, N = 735, zero free parameters. Statistics is 

**Held-out set:** 20% of genes withheld prior to analysis, stratified by sequence length. Sign preserved.

**Independent anchor set:** Picard et al. (2015). PNAS 112:E6854. 21/21 mitochondrial import phenotypes classified correctly. Zero training on Picard data.

---

## Reproducibility

```
Sequences  : UniProt Swiss-Prot (reviewed) — public domain
Masses     : AME2020 nuclear mass table — public domain
Constants  : CODATA 2018 — public domain
Derivation : Walker, J. (2026). DOI: 10.5281/zenodo.18210355
```

No proprietary data. No trained model. No hyperparameters.

---

### Citation

```bibtex
@dataset{walker2026infoton,
  author    = {Walker, January Natatia},
  title     = {An Infoton Dose of RxRx},
  year      = {2026},
  publisher = {Hugging Face},
  doi       = {10.5281/zenodo.18210355},
  url       = {https://huggingface.co/datasets/Infoton/An_Infoton_Dose_of_RxRx}
}

@article{walker2026infoton_eq,
  author  = {Walker, January Natatia},
  title   = {The Infoton: A Fundamental Particle of Information-Energy},
  year    = {2026},
  journal = {Infoton},
  doi     = {10.5281/zenodo.18210355}
}
```

---

## Contact

**Infoton, LLC**
Salt Lake City, Utah
https://infoton.ai
january@infoton.ai
[ORCID: 0009-0000-6843-2051](https://orcid.org/0009-0000-6843-2051)

---

An Infoton dose of RxRx