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SynLethDB 2.0: a web-based knowledge graph database on synthetic lethality for novel anticancer drug discovery
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Wnt/Ca2+/NFAT Signaling Maintains Survival of Ph+ Leukemia Cells upon Inhibition of Bcr-Abl
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DAISY: Picking Synthetic Lethals from Cancer Genomes
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A Genome-wide RNAi Screen Identifies Multiple Synthetic Lethal Interactions with the Ras Oncogene
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Predicting Cancer-Specific Vulnerability via Data-Driven Detection of Synthetic Lethality
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Gene Essentiality Profiling Reveals Gene Networks and Synthetic Lethal Interactions with Oncogenic Ras
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Combinatorial CRISPR-Cas9 Metabolic Screens Reveal Critical Redox Control Points Dependent on the KEAP1-NRF2 Regulatory Axis
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Parallel heuristics for scalable community detection
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Specific killing of BRCA2-deficient tumours with inhibitors of poly(ADP-ribose) polymerase
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Synergistic drug combinations for cancer identified in a CRISPR screen for pairwise genetic interactions
inferredcites →https://doi.org/10.1038/nchembio.1205openalex-snapshot
Systems-level antimicrobial drug and drug synergy discovery
inferredcites →https://doi.org/10.1038/ncomms15580openalex-snapshot
Systematic discovery of mutation-specific synthetic lethals by mining pan-cancer human primary tumor data
inferredcites →https://doi.org/10.1038/nm.4219openalex-snapshot
Genome-wide CRISPR screens reveal a Wnt–FZD5 signaling circuit as a druggable vulnerability of RNF43-mutant pancreatic tumors
inferredcites →https://doi.org/10.1038/nmeth.4225openalex-snapshot
Combinatorial CRISPR–Cas9 screens for de novo mapping of genetic interactions
inferredcites →https://doi.org/10.1038/nrc1691openalex-snapshot
The Concept of Synthetic Lethality in the Context of Anticancer Therapy
inferredcites →https://doi.org/10.1038/s41467-018-04647-1openalex-snapshot
Harnessing synthetic lethality to predict the response to cancer treatment
inferredcites →https://doi.org/10.1038/s41467-019-10215-yopenalex-snapshot
Optimal control nodes in disease-perturbed networks as targets for combination therapy
inferredcites →https://doi.org/10.1038/s41467-019-10751-7openalex-snapshot
Actomyosin-driven force patterning controls endocytosis at the immune synapse
inferredcites →https://doi.org/10.1038/s41467-021-21544-2openalex-snapshot
The tumor therapy landscape of synthetic lethality
inferredcites →https://doi.org/10.1073/pnas.1517883113openalex-snapshot
Multiplexed barcoded CRISPR-Cas9 screening enabled by CombiGEM
inferredcites →https://doi.org/10.1083/jcb.200309080openalex-snapshot
Novel regulation of mitotic exit by the Cdc42 effectors Gic1 and Gic2
inferredcites →https://doi.org/10.1093/bib/bbab058openalex-snapshot
siGCD: a web server to explore survival interaction of genes, cells and drugs in human cancers
inferredcites →https://doi.org/10.1093/bib/bbw142openalex-snapshot
A landscape of synthetic viable interactions in cancer
inferredcites →https://doi.org/10.1093/bib/bbx172openalex-snapshot
Link synthetic lethality to drug sensitivity of cancer cells
inferredcites →https://doi.org/10.1093/bioinformatics/btaa211openalex-snapshot
Dual-dropout graph convolutional network for predicting synthetic lethality in human cancers
inferredcites →https://doi.org/10.1093/bioinformatics/btab271openalex-snapshot
KG4SL: knowledge graph neural network for synthetic lethality prediction in human cancers
inferredcites →https://doi.org/10.1093/bioinformatics/bty673openalex-snapshot
DiscoverSL: an R package for multi-omic data driven prediction of synthetic lethality in cancers
inferredcites →https://doi.org/10.1093/bioinformatics/btz893openalex-snapshot
Predicting synthetic lethal interactions using heterogeneous data sources
inferredcites →https://doi.org/10.1093/genetics/31.3.269openalex-snapshot
GENETICS OF NATURAL POPULATIONS. XIII. RECOMBINATION AND VARIABILITY IN POPULATIONS OF DROSOPHILA PSEUDOOBSCURA
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Entrez Gene: gene-centered information at NCBI
inferredcites →https://doi.org/10.1093/nar/gks1170openalex-snapshot
GenomeRNAi: a database for cell-based and in vivo RNAi phenotypes, 2013 update
inferredcites →https://doi.org/10.1093/nar/gkv1072openalex-snapshot
BindingDB in 2015: A public database for medicinal chemistry, computational chemistry and systems pharmacology
inferredcites →https://doi.org/10.1093/nar/gkv1108openalex-snapshot
SynLethDB: synthetic lethality database toward discovery of selective and sensitive anticancer drug targets
inferredcites →https://doi.org/10.1093/nar/gkx1037openalex-snapshot
DrugBank 5.0: a major update to the DrugBank database for 2018
inferredcites →https://doi.org/10.1093/nar/gky1079openalex-snapshot
The BioGRID interaction database: 2019 update
inferredcites →https://doi.org/10.1093/nar/gkz1021openalex-snapshot
The DisGeNET knowledge platform for disease genomics: 2019 update
inferredcites →https://doi.org/10.1103/physreve.76.036106openalex-snapshot
Near linear time algorithm to detect community structures in large-scale networks
inferredcites →https://doi.org/10.1109/tcbb.2019.2909908openalex-snapshot
SL 2 MF: Predicting Synthetic Lethality in Human Cancers via Logistic Matrix Factorization
inferredcites →https://doi.org/10.1126/science.278.5340.1064openalex-snapshot
Integrating Genetic Approaches into the Discovery of Anticancer Drugs
inferredcites →https://doi.org/10.1128/mcb.01229-06openalex-snapshot
Small Interfering RNA Screens Reveal Enhanced Cisplatin Cytotoxicity in Tumor Cells Having both BRCA Network and TP53 Disruptions
inferredcites →https://doi.org/10.1158/0008-5472.can-12-1729openalex-snapshot
Novel DNA Damage Checkpoints Mediating Cell Death Induced by the NEDD8-Activating Enzyme Inhibitor MLN4924
inferredcites →https://doi.org/10.1172/jci8888openalex-snapshot
Choosing anticancer drug targets in the postgenomic era
inferredcites →https://doi.org/10.1186/s12859-019-2669-9openalex-snapshot
ElemCor: accurate data analysis and enrichment calculation for high-resolution LC-MS stable isotope labeling experiments
inferredcites →https://doi.org/10.1186/s12859-019-3197-3openalex-snapshot
Predicting synthetic lethal interactions in human cancers using graph regularized self-representative matrix factorization
inferredcites →https://doi.org/10.1186/s13059-019-1745-9openalex-snapshot
GEMINI: a variational Bayesian approach to identify genetic interactions from combinatorial CRISPR screens
inferredcites →https://doi.org/10.1186/s13062-015-0086-1openalex-snapshot
Inferring synthetic lethal interactions from mutual exclusivity of genetic events in cancer
inferredcites →https://doi.org/10.1371/journal.pone.0210859openalex-snapshot
Synthetic lethality guiding selection of drug combinations in ovarian cancer
inferredcites →https://doi.org/10.18632/oncotarget.10536openalex-snapshot
Ranking novel cancer driving synthetic lethal gene pairs using TCGA data
inferredcites →https://doi.org/10.18632/oncotarget.12046openalex-snapshot
Uncovering synthetic lethal interactions for therapeutic targets and predictive markers in lung adenocarcinoma
inferredcites →https://doi.org/10.2307/2533093openalex-snapshot
The Behavior of the P-Value When the Alternative Hypothesis is True
inferredcites →https://doi.org/10.3390/cancers11111682openalex-snapshot
SL-BioDP: Multi-Cancer Interactive Tool for Prediction of Synthetic Lethality and Response to Cancer Treatment
inferredcites →https://doi.org/10.48550/arxiv.1909.01315openalex-snapshot
Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks
inferredcites →https://doi.org/10.7554/elife.26726openalex-snapshot
Systematic integration of biomedical knowledge prioritizes drugs for repurposing
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/1873-3468.14950openalex-snapshot
Identifying actionable synthetically lethal cancer gene pairs using mutual exclusivity
inferred← citeshttps://doi.org/10.1002/mog2.70openalex-snapshot
The biological essence of synthetic lethality: Bringing new opportunities for cancer therapy
inferred← citeshttps://doi.org/10.1007/978-1-0716-4690-8_5openalex-snapshot
R-Based Protocols to Predict Synthetic Lethal Interactions in Cancers Using Machine Learning Tools
inferred← citeshttps://doi.org/10.1007/978-1-0716-5408-8_3openalex-snapshot
Using Biological Networks to Guide Biomedical Prediction
inferred← citeshttps://doi.org/10.1007/978-3-032-09321-9_17openalex-snapshot
MOSL: Integrating Multi-omics and Machine Learning to Predict Synthetic Lethality in Cancer Cell Lines
inferred← citeshttps://doi.org/10.1007/978-981-92-3441-7_37openalex-snapshot
Knowledge Graph-Enhanced Medical Large Language Models: Challenges, Methods, and Future Directions
inferred← citeshttps://doi.org/10.1007/978-981-95-0030-7_21openalex-snapshot
Multimodal GAN Integrating Hypergraph and Knowledge Graph Representations for Synthetic Lethality
inferred← citeshttps://doi.org/10.1007/s00412-025-00840-6openalex-snapshot
Sustainable integrative cell biology: CENP-C is guilty by association
inferred← citeshttps://doi.org/10.1007/s10577-025-09784-0openalex-snapshot
Sustainable integrative cell biology: CENP-C is guilty by association
inferred← citeshttps://doi.org/10.1016/b978-0-443-27523-4.00010-xopenalex-snapshot
Deep learning in personalized genomics and gene editing
inferred← citeshttps://doi.org/10.1016/j.artmed.2026.103519openalex-snapshot
MCKG-SL: Knowledge graph-based multi-feature cross-aggregation synthetic lethality prediction for KRAS gene
inferred← citeshttps://doi.org/10.1016/j.bcp.2026.117754openalex-snapshot
Unmasking the role of tumor microenvironment in the advanced stage of cancer treatment to mitigate risks during chemotherapy
inferred← citeshttps://doi.org/10.1016/j.csbj.2025.04.012openalex-snapshot
Struct2SL: Synthetic lethality prediction based on AlphaFold2 structure information and Multilayer Perceptron
inferred← citeshttps://doi.org/10.1016/j.gendis.2026.102057openalex-snapshot
ALDH2 inhibition induces synthetic lethality in APC-deficient colorectal cancer via ROS/ASK1/JNK pathway
inferred← citeshttps://doi.org/10.1016/j.knosys.2023.110752openalex-snapshot
SympGAN: A systematic knowledge integration system for symptom–gene associations network
inferred← citeshttps://doi.org/10.1016/j.nbt.2026.06.001openalex-snapshot
Harnessing computational intelligence for synthetic lethality: A roadmap from network biology to interpretable deep learning in precision oncology
inferred← citeshttps://doi.org/10.1016/j.neunet.2026.109516openalex-snapshot
Fast and featureless node representation learning with partial pairwise supervision
inferred← citeshttps://doi.org/10.1038/s41467-024-52900-7openalex-snapshot
Benchmarking machine learning methods for synthetic lethality prediction in cancer
inferred← citeshttps://doi.org/10.1038/s41551-025-01598-zopenalex-snapshot
Enhancing link prediction in biomedical knowledge graphs with BioPathNet
inferred← citeshttps://doi.org/10.1038/s41573-025-01273-7openalex-snapshot
Synthetic lethality in cancer drug discovery: challenges and opportunities
inferred← citeshttps://doi.org/10.1038/s41598-023-34161-4openalex-snapshot
Synthetic lethality prediction in DNA damage repair, chromatin remodeling and the cell cycle using multi-omics data from cell lines and patients.
inferred← citeshttps://doi.org/10.1038/s41598-024-71240-6openalex-snapshot
The molecular basis of the anticancer effect of statins
inferred← citeshttps://doi.org/10.1080/17501911.2025.2548756openalex-snapshot
Epigenetic synthetic lethality as a cancer therapeutic strategy: synergy of experimental and computational approaches
inferred← citeshttps://doi.org/10.1093/bib/bbae425openalex-snapshot
Synthetic lethal connectivity and graph transformer improve synthetic lethality prediction
inferred← citeshttps://doi.org/10.1093/bib/bbaf142openalex-snapshot
Interpretable high-order knowledge graph neural network for predicting synthetic lethality in human cancers
inferred← citeshttps://doi.org/10.1093/bib/bbaf255openalex-snapshot
TARGET-SL: precision essential gene prediction using driver prioritisation and synthetic lethality
inferred← citeshttps://doi.org/10.1093/bib/bbag470openalex-snapshot
GiGCN: a network-based framework for uncovering synthetic lethal and viable genetic interactions
inferred← citeshttps://doi.org/10.1093/bib/bbag564openalex-snapshot
Explainable/interpretable artificial intelligence and knowledge graph neural network for synthetic lethality prediction: overview, challenges, and future directions
inferred← citeshttps://doi.org/10.1093/bioinformatics/btac462openalex-snapshot
NSF4SL: negative-sample-free contrastive learning for ranking synthetic lethal partner genes in human cancers
inferred← citeshttps://doi.org/10.1093/bioinformatics/btac476openalex-snapshot
PiLSL: pairwise interaction learning-based graph neural network for synthetic lethality prediction in human cancers
inferred← citeshttps://doi.org/10.1093/bioinformatics/btad016openalex-snapshot
A heuristic algorithm solving the mutual-exclusivity-sorting problem
inferred← citeshttps://doi.org/10.1093/bioinformatics/btad261openalex-snapshot
KR4SL: knowledge graph reasoning for explainable prediction of synthetic lethality
inferred← citeshttps://doi.org/10.1093/bioinformatics/btae016openalex-snapshot
SL-Miner: a web server for mining evidence and prioritization of cancer-specific synthetic lethality
inferred← citeshttps://doi.org/10.1093/bioinformatics/btag337openalex-snapshot
Using cancer profiles to identify synthetic lethal therapeutic targets and predictive biomarkers in cancer gene dependency data
inferred← citeshttps://doi.org/10.1093/database/baac075openalex-snapshot
SLOAD: a comprehensive database of cancer-specific synthetic lethal interactions for precision cancer therapy via multi-omics analysis
inferred← citeshttps://doi.org/10.1093/database/baad036openalex-snapshot
BLAB2CancerKD: a knowledge graph database focusing on the association between lactic acid bacteria and cancer, but beyond
inferred← citeshttps://doi.org/10.1093/gigascience/giae082openalex-snapshot
Knowledge graph–based thought: a knowledge graph–enhanced LLM framework for pan-cancer question answering
inferred← citeshttps://doi.org/10.1093/nar/gkad806openalex-snapshot
SLKB: synthetic lethality knowledge base
inferred← citeshttps://doi.org/10.1093/nar/gkae993openalex-snapshot
CTR-DB 2.0: an updated cancer clinical transcriptome resource, expanding primary drug resistance and newly adding acquired resistance datasets and enhancing the discovery and validation of predictive biomarkers
inferred← citeshttps://doi.org/10.1093/narcan/zcag004openalex-snapshot
Advancing inducible gene-inactivation systems to explore synthetic lethality
inferred← citeshttps://doi.org/10.1093/nargab/lqae157openalex-snapshot
CancerPro: deciphering the pan-cancer prognostic landscape through combinatorial enrichment analysis and knowledge network insights
inferred← citeshttps://doi.org/10.1093/narmme/ugad001openalex-snapshot
Predicting host-based, synthetic lethal antiviral targets from omics data
inferred← citeshttps://doi.org/10.1093/pnasnexus/pgaf345openalex-snapshot
A genome-wide RNAi screen for novel CIN genes using human artificial chromosome
inferred← citeshttps://doi.org/10.1101/2022.07.07.499118openalex-snapshot
SLIDE-VIP: a comprehensive, cell line- and patient-based framework for synthetic lethality prediction in DNA damage repair, chromatin remodeling and cell cycle
inferred← citeshttps://doi.org/10.1101/2023.09.13.557545openalex-snapshot
Cell context-specific Synthetic lethality Prediction and Mechanism Analysis
inferred← citeshttps://doi.org/10.1101/2024.06.17.599219openalex-snapshot
Path-based reasoning for biomedical knowledge graphs with BioPathNet
inferred← citeshttps://doi.org/10.1101/2024.08.17.608400openalex-snapshot
Recon8D: A metabolic regulome network from oct-omics and machine learning
inferred← citeshttps://doi.org/10.1101/2024.11.20.624509openalex-snapshot
Driver-associated transcriptional rewiring reveals conditional genetic vulnerabilities in cancer
inferred← citeshttps://doi.org/10.1101/2025.09.08.674723openalex-snapshot
Translating clinical gene sequencing into a foundational representation of tumor subtype
inferred← citeshttps://doi.org/10.1109/aixmhc65380.2025.00014openalex-snapshot
Computational Integration of Synthetic Lethality Networks and Traditional Chinese Medicine: In Silico Identification of Novel Therapeutic Strategies for Lung Adenocarcinoma
inferred← citeshttps://doi.org/10.1109/embc58623.2025.11252721openalex-snapshot
Multi-view Contrastive Learning for Cell Line-specific Synthetic Lethality Prediction
inferred← citeshttps://doi.org/10.1109/embc58623.2025.11254053openalex-snapshot
SL-MERK: Synthetic Lethality Mechanism Explainer based on GraphRAG and Knowledge Graph
inferred← citeshttps://doi.org/10.1109/embc58623.2025.11254319openalex-snapshot
ESM4SL: Protein Language Models for Cancer Cell Line-specific Synthetic Lethality Prediction
inferred← citeshttps://doi.org/10.1109/ickg59574.2023.00037openalex-snapshot
Meta Learning for Low-Data Prediction of Cancer-Specific Synthetic Lethality as Drug Targets
inferred← citeshttps://doi.org/10.1109/smc54092.2024.10830943openalex-snapshot
DSESL: A Deep Stacking Ensemble Model for Synthetic Lethality Prediction
inferred← citeshttps://doi.org/10.1109/tcbbio.2025.3617331openalex-snapshot
Learning Universal Knowledge Graph Embedding for Predicting Biomedical Pairwise Interactions
inferred← citeshttps://doi.org/10.1109/tcbbio.2025.3626526openalex-snapshot
An Interpretable Complex Knowledge Multi-Hop Reasoning Model for Predicting Synthetic Lethality in Human Cancers
inferred← citeshttps://doi.org/10.1109/tcbbio.2025.3631499openalex-snapshot
KG-SLomics: Synthetic Lethality Prediction Using Knowledge Graph and Cancer Type-Specific Multiomics Integrated Graph Neural Network
inferred← citeshttps://doi.org/10.1145/3807503.3819499openalex-snapshot
SLAMR: LLM-Augmented Multimodal Learning for Cold-Start Synthetic Lethality Recommendation in Cancer Cell Lines
inferred← citeshttps://doi.org/10.1145/3807503.3819571openalex-snapshot
GenoME-SL: Genomic-LLM Fused Mechanism Explanation Framework for Synthetic Lethality
inferred← citeshttps://doi.org/10.1158/2159-8290.cd-23-0388openalex-snapshot
Large-scale Pan-cancer Cell Line Screening Identifies Actionable and Effective Drug Combinations
inferred← citeshttps://doi.org/10.1186/s12859-025-06345-4openalex-snapshot
MGANSL: multi-network representation generating with generative adversarial network for synthetic lethality prediction
inferred← citeshttps://doi.org/10.1186/s12964-025-02602-4openalex-snapshot
Mutation-informed gene pairs to predict melanoma metastasis
inferred← citeshttps://doi.org/10.1186/s13059-025-03501-0openalex-snapshot
PRODE recovers essential and context-essential genes through neighborhood-informed scores
inferred← citeshttps://doi.org/10.1186/s40537-023-00774-9openalex-snapshot
Healthcare knowledge graph construction: A systematic review of the state-of-the-art, open issues, and opportunities
inferred← citeshttps://doi.org/10.1200/po-25-00035openalex-snapshot
Synthetic Lethal Co-Mutations in DNA Damage Response Pathways Predict Response to Immunotherapy in Pan-Cancer
inferred← citeshttps://doi.org/10.1371/journal.pcbi.1012336openalex-snapshot
MAGICAL: A multi-class classifier to predict synthetic lethal and viable interactions using protein-protein interaction network
inferred← citeshttps://doi.org/10.1371/journal.pcbi.1013351openalex-snapshot
Mutations in tumor signaling, metastases, and synthetic lethality establish distinct patterns
inferred← citeshttps://doi.org/10.1371/journal.pcbi.1013547openalex-snapshot
A multi-layer encoder prediction model for individual sample specific gene combination effect (MLEC-iGeneCombo)
inferred← citeshttps://doi.org/10.3389/fgene.2022.961611openalex-snapshot
Synthetic lethal gene pairs: Experimental approaches and predictive models
inferred← citeshttps://doi.org/10.3389/fphar.2024.1398231openalex-snapshot
MPASL: multi-perspective learning knowledge graph attention network for synthetic lethality prediction in human cancer
inferred← citeshttps://doi.org/10.3390/cimb48050475openalex-snapshot
A Synthetic Lethality-Informed Multi-Omic Framework for Identifying a Five-Gene Diagnostic Signature in Chronic Obstructive Pulmonary Disease
inferred← citeshttps://doi.org/10.3390/ijms25179576openalex-snapshot
Non-Negative Matrix Tri-Factorization for Representation Learning in Multi-Omics Datasets with Applications to Drug Repurposing and Selection
inferred← citeshttps://doi.org/10.3390/ijms26199530openalex-snapshot
Identification of Anticancer Targets in Ovarian Cancer Using Genomic Drug Sensitivity Data
inferred← citeshttps://doi.org/10.48130/targetome-0026-0001openalex-snapshot
Data-driven targetome discovery and database requirements: insights from the therapeutic target database
inferred← citeshttps://doi.org/10.5204/thesis.eprints.242358openalex-snapshot
Protein-coding potential of non-coding regions in the human genome
inferred← citeshttps://doi.org/10.64898/2026.02.03.703397openalex-snapshot
Mutational signatures in cancer genomes alter protein sequence motifs in cellular signaling networks
inferred← citeshttps://doi.org/10.64898/2026.02.25.708096openalex-snapshot
Uncertainty-aware synthetic lethality prediction with pretrained foundation models
inferred← citeshttps://doi.org/10.64898/2026.04.14.718563openalex-snapshot
Pairwise genomic alterations identify prognostic tumor states in multiple cancer types
inferred← citeshttps://doi.org/10.70675/e78139f1z6c9bz45d3z8957z90a81b8ab70fopenalex-snapshot
Application of translational research to the study of biological functions associated with stress resistance and adaptation to agroecological cropping systems in pulses
inferred← citeshttps://doi.org/10.71150/jm.2512017openalex-snapshot
Synthetic rescue in Saccharomyces cerevisiae: Concepts, large-scale genetic mapping, and functional implications
inferred← citeshttps://doi.org/10.7150/ijms.90829openalex-snapshot
Text Mining and Drug Discovery Analysis: A Comprehensive Approach to Investigate Diabetes-Induced Osteoporosis
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