Paper Citation Record · LEDGER

HyperNetWalk: A Unified Framework for Personalized and Cohort-Level Cancer Driver Gene Identification via Reverse Inference on Layered Signaling-Regulatory Network

As of 19 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2601.01337.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2601.01337 v2

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T12:59:44.133645Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

24 of 24 outbound references displayed

verified exact0
verified fuzzy0
unresolved24
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bd42f77b-fe1e-4857-b80e-00e6bb91d8ad · outbound

This paper cites Lawrence, Petar Stojanov, Paz Polak, Gregory V.

HyperNetWalk: A Unified Framework for Personalized and Cohort-Level Cancer Driver Gene Identification via Reverse Inference on Layered Signaling-Regulatory Network Lawrence, Petar Stojanov, Paz Polak, Gregory V

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T12:59:42.437862Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66b99b83-31b6-4c30-9ea9-92516deeab87 · outbound

This paper cites Driverml: a machine learning algorithm for identifying driver genes in cancer sequencing studies.

HyperNetWalk: A Unified Framework for Personalized and Cohort-Level Cancer Driver Gene Identification via Reverse Inference on Layered Signaling-Regulatory Network Driverml: a machine learning algorithm for identifying driver genes in cancer sequencing studies

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T12:59:42.498592Z

Source-reported events for the cited work

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Observation f36a1964-7df2-47e7-9e46-7d82cc8778bd · outbound

This paper cites Oncodrivefml: a general framework to identify coding and non-coding regions with cancer driver mutations.

HyperNetWalk: A Unified Framework for Personalized and Cohort-Level Cancer Driver Gene Identification via Reverse Inference on Layered Signaling-Regulatory Network Oncodrivefml: a general framework to identify coding and non-coding regions with cancer driver mutations

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T12:59:42.563311Z

Source-reported events for the cited work

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Observation e785d419-b7e5-4cae-b39e-4491b229fe41 · outbound

This paper cites Identification of cancer driver genes based on nucleotide context.

HyperNetWalk: A Unified Framework for Personalized and Cohort-Level Cancer Driver Gene Identification via Reverse Inference on Layered Signaling-Regulatory Network Identification of cancer driver genes based on nucleotide context

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T12:59:42.630712Z

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Observation 2534e1d3-0c0c-4118-a05f-fbdf9ae91be5 · outbound

This paper cites Integration of multi- omics data with graph convolutional networks to identify new cancer genes and their associated molecular mechanisms.

HyperNetWalk: A Unified Framework for Personalized and Cohort-Level Cancer Driver Gene Identification via Reverse Inference on Layered Signaling-Regulatory Network Integration of multi- omics data with graph convolutional networks to identify new cancer genes and their associated molecular mechanisms

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T12:59:42.697630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce501b16-c78a-4847-a15a-dade823ff25b · outbound

This paper cites Imi-driver: integrating multi-level gene networks and multi-omics for cancer driver gene identification.

HyperNetWalk: A Unified Framework for Personalized and Cohort-Level Cancer Driver Gene Identification via Reverse Inference on Layered Signaling-Regulatory Network Imi-driver: integrating multi-level gene networks and multi-omics for cancer driver gene identification

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T12:59:42.751527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e41e226-a095-4502-84c4-2f768eb1d6bc · outbound

This paper cites Pan-cancer network analysis identifies combinations of rare somatic mutations across pathways and protein complexes.

HyperNetWalk: A Unified Framework for Personalized and Cohort-Level Cancer Driver Gene Identification via Reverse Inference on Layered Signaling-Regulatory Network Pan-cancer network analysis identifies combinations of rare somatic mutations across pathways and protein complexes

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T12:59:42.805234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27d15e37-bcd4-470c-82d4-c1294c2d034d · outbound

This paper cites Drivernet: uncovering the impact of somatic driver mutations on transcriptional networks in cancer.

HyperNetWalk: A Unified Framework for Personalized and Cohort-Level Cancer Driver Gene Identification via Reverse Inference on Layered Signaling-Regulatory Network Drivernet: uncovering the impact of somatic driver mutations on transcriptional networks in cancer

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T12:59:42.859318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 615f57b2-b8bd-4701-a491-00858d964504 · outbound

This paper cites Velculescu, Shibin Zhou, Luis A.

HyperNetWalk: A Unified Framework for Personalized and Cohort-Level Cancer Driver Gene Identification via Reverse Inference on Layered Signaling-Regulatory Network Velculescu, Shibin Zhou, Luis A

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T12:59:42.913595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba246998-3069-4f32-8f1a-31a92b208d7f · outbound

This paper cites Dawnrank: discovering personalized driver genes in cancer.

HyperNetWalk: A Unified Framework for Personalized and Cohort-Level Cancer Driver Gene Identification via Reverse Inference on Layered Signaling-Regulatory Network Dawnrank: discovering personalized driver genes in cancer

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T12:59:43.012602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f43a3b5-be45-4103-8911-d8b1e7d89246 · outbound

This paper cites Discovering personalized driver mutation profiles of single samples in cancer by network control strategy.

HyperNetWalk: A Unified Framework for Personalized and Cohort-Level Cancer Driver Gene Identification via Reverse Inference on Layered Signaling-Regulatory Network Discovering personalized driver mutation profiles of single samples in cancer by network control strategy

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T12:59:43.131429Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d71fd85-8714-4805-9677-bb10dd88b329 · outbound

This paper cites Personadrive: a method for the identification and prioritization of personalized cancer drivers.

HyperNetWalk: A Unified Framework for Personalized and Cohort-Level Cancer Driver Gene Identification via Reverse Inference on Layered Signaling-Regulatory Network Personadrive: a method for the identification and prioritization of personalized cancer drivers

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T12:59:43.236267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4a6ef17-2c99-4174-8d71-29e2c4573c2b · outbound

This paper cites A novel hypergraph model for identifying and prioritizing personalized drivers in cancer.

HyperNetWalk: A Unified Framework for Personalized and Cohort-Level Cancer Driver Gene Identification via Reverse Inference on Layered Signaling-Regulatory Network A novel hypergraph model for identifying and prioritizing personalized drivers in cancer

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T12:59:43.362995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 782df696-5f13-41dd-b611-4f8141a6d691 · outbound

This paper cites Drivermp enables improved identification of cancer driver genes.

HyperNetWalk: A Unified Framework for Personalized and Cohort-Level Cancer Driver Gene Identification via Reverse Inference on Layered Signaling-Regulatory Network Drivermp enables improved identification of cancer driver genes

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T12:59:43.487900Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fbcc7566-7b63-4cb7-92c1-bf783786aa67 · outbound

This paper cites Pitch: A pathway-induced prioritization of personalized cancer driver genes based on higher-order interactions.

HyperNetWalk: A Unified Framework for Personalized and Cohort-Level Cancer Driver Gene Identification via Reverse Inference on Layered Signaling-Regulatory Network Pitch: A pathway-induced prioritization of personalized cancer driver genes based on higher-order interactions

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T12:59:43.577389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fcbb0a07-4944-4137-b9b7-b91e0597e15d · outbound

This paper cites Prodigy: personalized prioritization of driver genes.

HyperNetWalk: A Unified Framework for Personalized and Cohort-Level Cancer Driver Gene Identification via Reverse Inference on Layered Signaling-Regulatory Network Prodigy: personalized prioritization of driver genes

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T12:59:43.704364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c4017d2-e48b-469f-ba89-915657f6b0ec · outbound

This paper cites Driver- rwh: discovering cancer driver genes by random walk on a gene mutation hypergraph.

HyperNetWalk: A Unified Framework for Personalized and Cohort-Level Cancer Driver Gene Identification via Reverse Inference on Layered Signaling-Regulatory Network Driver- rwh: discovering cancer driver genes by random walk on a gene mutation hypergraph

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T12:59:43.774979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e13d47f8-2cdd-40b8-b4b0-e35cf23f5e60 · outbound

This paper cites A random walk-based method to identify driver genes by integrating the subcellular localization and variation frequency into bipartite graph.

HyperNetWalk: A Unified Framework for Personalized and Cohort-Level Cancer Driver Gene Identification via Reverse Inference on Layered Signaling-Regulatory Network A random walk-based method to identify driver genes by integrating the subcellular localization and variation frequency into bipartite graph

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T12:59:43.904073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f74b9cc-8e24-4613-af21-4ebf8c1425b6 · outbound

This paper cites Visualizing and interpreting cancer genomics data via the xena platform.

HyperNetWalk: A Unified Framework for Personalized and Cohort-Level Cancer Driver Gene Identification via Reverse Inference on Layered Signaling-Regulatory Network Visualizing and interpreting cancer genomics data via the xena platform

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T12:59:43.978111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67008f61-7b9b-451e-a9fc-81324621c40b · outbound

This paper cites The string database in 2023: protein–protein association networks and functional enrichment analyses for any sequenced genome of interest.

HyperNetWalk: A Unified Framework for Personalized and Cohort-Level Cancer Driver Gene Identification via Reverse Inference on Layered Signaling-Regulatory Network The string database in 2023: protein–protein association networks and functional enrichment analyses for any sequenced genome of interest

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T12:59:44.072949Z

Source-reported events for the cited work

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Observation 9303e2ed-3b87-4bc1-9709-7d1956b6b2bd · outbound

This paper cites Regnetwork 2025: an in- tegrative data repository for gene regulatory networks in human and mouse.

HyperNetWalk: A Unified Framework for Personalized and Cohort-Level Cancer Driver Gene Identification via Reverse Inference on Layered Signaling-Regulatory Network Regnetwork 2025: an in- tegrative data repository for gene regulatory networks in human and mouse

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T12:59:44.076496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c623304f-537e-4b65-a1eb-40bd7d001676 · outbound

This paper cites Wesme: uncovering mutual exclusivity of cancer drivers and beyond.

HyperNetWalk: A Unified Framework for Personalized and Cohort-Level Cancer Driver Gene Identification via Reverse Inference on Layered Signaling-Regulatory Network Wesme: uncovering mutual exclusivity of cancer drivers and beyond

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T12:59:44.080146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b17285e-1324-4ca5-81e7-8b0ade0e1ddf · outbound

This paper cites Random walks on hyper- graphs.

HyperNetWalk: A Unified Framework for Personalized and Cohort-Level Cancer Driver Gene Identification via Reverse Inference on Layered Signaling-Regulatory Network Random walks on hyper- graphs

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T12:59:44.100346Z

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Unavailable: canonical work link unavailable.

Observation 12a4675d-06e5-4a11-a1d5-d8e6e2db84a4 · outbound

This paper cites The cosmic cancer gene census: describing genetic dysfunction across all human cancers.

HyperNetWalk: A Unified Framework for Personalized and Cohort-Level Cancer Driver Gene Identification via Reverse Inference on Layered Signaling-Regulatory Network The cosmic cancer gene census: describing genetic dysfunction across all human cancers

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T12:59:44.133645Z

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Pith citing papers

No inbound Pith citation observations are available.