Independent open research

BIOLOGY. DATA.POSSIBILITY.

SetNet is an independent, non-commercial research initiative exploring DNA, methylation, and their relationship to cancer biology through genomic and cellular sequencing.

For research purposes only

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Whole-genomesequencing

Investigating genomic variation and methylation patterns across the full DNA sequence.

Nanoporesequencing

Exploring long-read approaches for genomic structure, variation, and methylation patterns.

Single-cellsequencing

Resolving variation cell by cell to examine biological heterogeneity.

Cancer genomesequencing

Investigating genomic changes and distinct molecular patterns in cancer biology.

Sequencing focus

Nanoporesequencing.

An educational look at how DNA can pass through a nanoscale pore during sequencing. SetNet's interest is exploratory and focused on research applications.

Educational explainer / research context

Optional video explainerHow Oxford Nanopore sequencing worksWatch on YouTube · Oxford Nanopore Technologies

Research direction

DNA. Methylation.Cancer biology.

SetNet investigates how DNA and methylation patterns relate to cancer biology and how those patterns may change across research time points.

The aim is to explore recurring signals as candidate biomarkers within distinct biological contexts.

All data collected and presented are for research purposes only.

Current inquiries

Questions inprogress.

Updated August 2026

Useful collaboration includes de-identified datasets, reproducible methods, comparative analysis, and research perspectives across these areas.

01 / Longitudinal

How do methylation patterns change across research time points?

02 / Biomarkers

Which recurring signals may warrant further biomarker investigation?

03 / Comparative biology

What can twin comparisons reveal about differing cancer biology?

Multimodal research

Studying change.Across signals.

SetNet is exploring how de-identified molecular trends and imaging may be examined together across research time points.

Research presentation / not medical advice

De-identified longitudinal visualization of liver function and circulating tumor DNA research data — Longitudinal research dataMolecular and biochemical trends across time

Chart context

This de-identified research view places alkaline phosphatase, AST, ALT, and circulating tumor DNA measurements on one longitudinal timeline.

Coverage shown: May 2023–June 2026
Research use: Comparison across time points
Interpretation: Exploratory; not medical advice

Source labels and reference ranges remain visible in the full-resolution chart. Underlying methods and structured data have not yet been published.

De-identified multi-view research imaging of the brain — Cross-sectional imagingMultiple planes

De-identified volumetric research imaging from an upper perspective — Volumetric imagingSpatial view A

De-identified volumetric research imaging from a lateral perspective — Volumetric imagingSpatial view B

Research visuals

Every image.In context.

Explore SetNet's de-identified research imagery and clearly labeled conceptual studies in one intentional visual collection.

Explore the visual collection

Microscopy image of blood featuring a white blood cell — Original microscopyBlood and white blood cell

Original abstract visualization of three cellular states observed across research time points — Three research time points / one evolving biological context

A longitudinal view

Snapshots show moments.Time reveals change.

Comparing DNA and methylation data across research time points can help researchers observe change.

Emerging inquiry

Digital twins.Biological twins.

SetNet is investigating the emerging field of digital twins alongside comparative research involving biological twins.

One question guides this work: why can cancer develop in one twin while the other does not?

Exploratory research / evolving methods

How we explore

From sequence.To signal.

Sequence

Explore genomic and cellular material using research sequencing approaches.

Compare

Create DNA snapshots across time points and examine methylation patterns and change.

Investigate

Study recurring signals as research candidates within distinct biological contexts.

Connect

Continue theconversation.

SetNet welcomes fellow researchers and curious collaborators interested in genome sequencing, methylation, longitudinal comparison, and candidate biomarker discovery.

Contact about the research