← back

A Deterministic Binary Fingerprinting Framework with Zero-Trained Feature Extrac

Sparse count matrices from single-cell transcriptomes to k-mer profiles and document-term frequencies are conventionally analyzed via PCA-reduced graph clustering or iterative optimization in continuous embedding spaces. We introduce MMTB,

https://arxiv.org/abs/2607.14596v1 ↗
Thesis fit
Good fit

Within your typical scope; diligence still required.

Edit thesis
In your usual scope
Idea match None

How close the company’s idea is to your thesis statement

Sector ai

Overlap with sectors you care about

Geography Unknown

Location unknown — scores 0

Your thesis: “We back exceptional technical founders building AI-first products and infrastructure, deploying $100K checks within 24 hours.”

Founder → stable Traction → stable Idea vs market → stable
Generate memo
Add / edit details

Correct facts used on the next screening or memo.

Similar baseline plays (YC · idea space)

Blank Bio · Active
RNA intelligence for precision medicine
founders not scraped yet
Spiral Genetics · Inactive
Large Scale Genomic Data Mining Software
founders not scraped yet
CellChorus · Active
The dynamic single-cell analysis company
founders not scraped yet
HistoWiz · Active
Accelerating Histopathology for Cancer Research
founders not scraped yet