Paper Citation Record · LEDGER

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics

As of 10 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 1 inbound Pith citation observation for arXiv:2502.01012.

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

pith.paper-citation-record.v1
2502.01012 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T17:02:06.952811Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T17:02:06.952811Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-09T17:02:06.994813Z

Reference resolution

37 of 37 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b96b344f-b833-4334-a167-ab0625da0d5b · outbound

This paper cites A review of uncertainty quantification in deep learning: Techniques, applications and challenges.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics A review of uncertainty quantification in deep learning: Techniques, applications and challenges

Reference 1

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Source-reported events for the cited work

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Observation b051fb4c-45f4-4018-97f8-53f6d2906979 · outbound

This paper cites Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds

Reference 2

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Observation 63f99843-0662-492e-b092-6e0ee766501b · outbound

This paper cites A quantitative genetic interaction map of hiv infection.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics A quantitative genetic interaction map of hiv infection

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:02:07.593977Z

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Observation a7d9c273-d655-4f12-bfab-2b272c7ff26c · outbound

This paper cites CRISPR-GPT for Agentic Automation of Gene-editing Experiments.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics CRISPR-GPT for Agentic Automation of Gene-editing Experiments

Reference 4

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Observation 561a6c95-be40-44ce-a125-43753a86b3f0 · outbound

This paper cites Sequential optimal experimental design of perturbation screens guided by multi-modal priors.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics Sequential optimal experimental design of perturbation screens guided by multi-modal priors

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:02:07.575504Z

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Observation 430ee22c-3bd1-4794-9bde-7aad390bff39 · outbound

This paper cites Robust estimation of a location param- eter.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics Robust estimation of a location param- eter

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:02:07.559271Z

Source-reported events for the cited work

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Observation b1beac42-ba09-4965-bff3-1976cf5dffba · outbound

This paper cites Automated Discovery of Pairwise Interactions from Unstructured Data.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics Automated Discovery of Pairwise Interactions from Unstructured Data

Reference 7

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Observation cd18f135-bb70-4d4e-a8f4-68d654765482 · outbound

This paper cites Active learning to discover pairwise genetic interac- tions via representation learning.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics Active learning to discover pairwise genetic interac- tions via representation learning

Reference 8

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Observation acdde672-be8d-4b17-a250-1a2f0fc0f9db · outbound

This paper cites Bilinear bandits with low-rank structure.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics Bilinear bandits with low-rank structure

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:02:07.528257Z

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Observation 1b6bc915-cd35-47fc-872c-7d45fb1386d7 · outbound

This paper cites Goatools: A python library for gene ontology analyses.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics Goatools: A python library for gene ontology analyses

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:02:07.512748Z

Source-reported events for the cited work

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Observation e8d48fa9-2d9d-420d-9e8f-0dfa32c9dc4f · outbound

This paper cites Simple and scalable predictive uncertainty es- timation using deep ensembles.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics Simple and scalable predictive uncertainty es- timation using deep ensembles

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:02:07.490327Z

Source-reported events for the cited work

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Observation 9430d579-0930-4360-ac8e-d999ccc34c8d · outbound

This paper cites Discobax dis- covery of optimal intervention sets in genomic experiment design.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics Discobax dis- covery of optimal intervention sets in genomic experiment design

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:02:07.471070Z

Source-reported events for the cited work

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Observation 7bf48873-8a0d-4248-a8c8-911c7618f65b · outbound

This paper cites GeneDisco: A Benchmark for Experimental Design in Drug Discovery.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics GeneDisco: A Benchmark for Experimental Design in Drug Discovery

Reference 13

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Observation cbcb029b-ffc1-470e-a2c7-19afd564fcf5 · outbound

This paper cites Neural collapse with unconstrained features.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics Neural collapse with unconstrained features

Reference 14

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Observation 08e62e92-95ae-474e-9810-bfa04315794b · outbound

This paper cites The scalable precision medicine open knowledge engine (spoke): a massive knowledge graph of biomedical information.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics The scalable precision medicine open knowledge engine (spoke): a massive knowledge graph of biomedical information

Reference 15

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Source-reported events for the cited work

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Observation 7e180045-8d7f-4654-8edc-8bdef067d076 · outbound

This paper cites Exploring genetic interaction mani- folds constructed from rich single-cell phenotypes.Science, 365(6455):786–793, 2019.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics Exploring genetic interaction mani- folds constructed from rich single-cell phenotypes.Science, 365(6455):786–793, 2019

Reference 16

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Source-reported events for the cited work

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Observation 6ceea521-45e8-41aa-aa07-f06a789ca6a3 · outbound

This paper cites Neural design for genetic perturbation ex- periments.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics Neural design for genetic perturbation ex- periments

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:02:07.407247Z

Source-reported events for the cited work

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Observation 6e7b5f32-1be1-43bf-8cb0-3dd80de703c2 · outbound

This paper cites Deep- walk: Online learning of social representations.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics Deep- walk: Online learning of social representations

Reference 18

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Observation 297f77c8-edab-4897-b8c0-4c9c23d4af96 · outbound

This paper cites Optimal design of experiments.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics Optimal design of experiments

Reference 19

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Observation f54831a0-049e-4174-add3-6db360454b67 · outbound

This paper cites A crispr toolbox to study virus–host in- teractions.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics A crispr toolbox to study virus–host in- teractions

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:02:07.364723Z

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Observation 0f2ff645-dac3-421d-8df4-12ba98dfdbc3 · outbound

This paper cites Hiv tat controls rna polymerase ii and the epigenetic landscape to transcrip- tionally reprogram target immune cells.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics Hiv tat controls rna polymerase ii and the epigenetic landscape to transcrip- tionally reprogram target immune cells

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:02:07.349043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4bfc19d1-4dd3-4fa8-8587-c8596e6f495b · outbound

This paper cites Mapping information-rich genotype- phenotype landscapes with genome-scale perturb-seq.Cell, 185(14):2559–2575, 2022.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics Mapping information-rich genotype- phenotype landscapes with genome-scale perturb-seq.Cell, 185(14):2559–2575, 2022

Reference 22

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Source-reported events for the cited work

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Observation 69d0fb13-22c2-46c7-87f0-87fea45cae1f · outbound

This paper cites Antiviral ther- apy.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics Antiviral ther- apy

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:02:07.316293Z

Source-reported events for the cited work

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Observation 843005f4-c2ea-4dcb-954b-8c33d4d923ba · outbound

This paper cites Best arm identification in graphical bi- linear bandits.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics Best arm identification in graphical bi- linear bandits

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:02:07.297378Z

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Observation 8631d709-1d52-4242-8694-bdf5ce168268 · outbound

This paper cites BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments

Reference 25

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Observation 13eb10d7-aca1-4867-b922-e055d3fff184 · outbound

This paper cites A Survey on Oversmoothing in Graph Neural Networks.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics A Survey on Oversmoothing in Graph Neural Networks

Reference 26

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Observation 5657b824-c9d2-428a-8c78-5074cbb531ed · outbound

This paper cites Modeling re- lational data with graph convolutional networks.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics Modeling re- lational data with graph convolutional networks

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:02:07.281208Z

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Observation 10c071d3-ef97-4274-af84-cd1d138f8c4e · outbound

This paper cites Dropout: a sim- ple way to prevent neural networks from overfitting.The journal of machine learning research, 15(1):1929–1958, 2014.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics Dropout: a sim- ple way to prevent neural networks from overfitting.The journal of machine learning research, 15(1):1929–1958, 2014

Reference 28

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Observation 8762be2f-7db2-41e8-a8b6-538e53b68534 · outbound

This paper cites A review of active learning approaches to experimental design for uncover- ing biological networks.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics A review of active learning approaches to experimental design for uncover- ing biological networks

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:02:07.244157Z

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Observation bc7b609f-3079-43f6-9755-933fe61ce8a4 · outbound

This paper cites Hiv-1 antiretrovi- ral resistance: scientific principles and clinical applications.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics Hiv-1 antiretrovi- ral resistance: scientific principles and clinical applications

Reference 30

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Observation 4e102a0d-104c-4264-8ae0-220cb7366965 · outbound

This paper cites Complex embeddings for simple link prediction.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics Complex embeddings for simple link prediction

Reference 31

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Observation 6611e46f-ddb8-41e6-9de6-ccea87a8881a · outbound

This paper cites Hallucination is Inevitable: An Innate Limitation of Large Language Models.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics Hallucination is Inevitable: An Innate Limitation of Large Language Models

Reference 32

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Observation 0e95724b-e9d4-41c7-8fc3-de9b4925cd2d · outbound

This paper cites Embedding Entities and Relations for Learning and Inference in Knowledge Bases.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics Embedding Entities and Relations for Learning and Inference in Knowledge Bases

Reference 33

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Observation ac96e1a1-592c-4488-b679-1096f1e0ee03 · outbound

This paper cites Towards deeper graph neural net- works with differentiable group normalization.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics Towards deeper graph neural net- works with differentiable group normalization

Reference 34

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Observation 8d28851e-ba38-458b-8f63-7f36a07fc10d · outbound

This paper cites A Geometric Analysis of Neural Collapse with Unconstrained Features.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics A Geometric Analysis of Neural Collapse with Unconstrained Features

Reference 35

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Observation ad5a8742-7805-40ed-8615-0f3229959406 · outbound

This paper cites Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics

Reference 2022

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Observation 397aa815-5a46-44fe-9c04-d8cb44a75106 · outbound

This paper cites Mary Silvareceived an M.S.

Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics Mary Silvareceived an M.S

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:02:07.184415Z

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Pith citing papers

Observation ad5a8742-7805-40ed-8615-0f3229959406 · inbound