SetNetContact

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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01

Whole-genome sequencing

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

02

Nanopore sequencing

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

03

Single-cell sequencing

Resolving variation cell by cell to examine biological heterogeneity.

04

Cancer genome sequencing

Investigating genomic changes and distinct molecular patterns in cancer biology.

Sequencing focus

Nanopore sequencing.
At molecular scale.

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
Molecular illustration of DNA passing through a nanopore in a membrane
Nanopore sequencingMolecular-scale illustration

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.

Multimodal research

Assessing tumor growth.
Across multiple research 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
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
Microscopy image of blood featuring a white blood cell
Original microscopyBlood and white blood cell
Original conceptual visualization of a cancer-cell model and its internal structure
Cancer biologyCellular structure

Research lenses

From cellular structure.
To chromatin state.

Original visual studies frame biological structures and processes that inform SetNet's research direction.

Original conceptual visualization of a cell progressing through late mitosis
Cell divisionLate mitosis
Original conceptual visualization of a cell constricting during cytokinesis
Cell divisionCytokinesis
Original conceptual visualization of cellular architecture and internal organization
Cellular structureInternal organization
Original conceptual visualization of chromatin with selected methylation sites
Epigenetic contextMethylation sites
Original conceptual visualization of an open chromatin state
Chromatin stateOpen structure
Original conceptual visualization of a compact chromatin state
Chromatin stateCompact structure
Original abstract visualization of three cellular states observed across research time points
Three research time points / one evolving biological context

A longitudinal view

One sequence captures a moment. Connected DNA and methylation snapshots can help reveal change over time.

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.

01

Sequence

Explore genomic and cellular material using research sequencing approaches.

02

Compare

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

03

Investigate

Study recurring signals as research candidates within distinct biological contexts.

Connect

Let's share what changes—and what persists.

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

Connect around the research