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Pairwise interactions between perturbations to a system can provide evidence for the causal dependencies of the underlying underlying mechanisms of a system.
Proteasome inhibitors block dna repair and radiosensitize non-small cell lung cancer
K. R. Cron, K. Zhu, D. S. Kushwaha, G. Hsieh, D. Merzon, J. Rameseder, C. C. Chen, A. D. D’Andrea, and D. Kozono · 1932
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On a measure of the information provided by an experiment
D. V. Lindley · 1956
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Asymptotic evaluation of certain markov process expectations for large time. iv
M. D. Donsker and S. S. Varadhan · 1983
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Nonlinear independent component analysis: Existence and uniqueness results
A. Hyvärinen and P. Pajunen · 1999
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Maximum entropy sampling and optimal bayesian experimental design
P. Sebastiani and H. P. Wynn · 2000
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High-throughput screening goes to school
A. Dove · 2007
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Geometric integration theory
S. G. Krantz and H. R. Parks · 2008
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Sleeping experts and bandits with stochastic action availability and adversarial rewards
V. Kanade, H. B. McMahan, and B. Bryan · 2009
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Matrix completion problems
M. Laurent · 2009
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Divergence estimation for multidimensional densities via k k -nearest-neighbor distances
Q. Wang, S. R. Kulkarni, and S. Verdú · 2009
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Synthetic lethality: General principles, utility and detection using genetic screens in human cells
S. M. Nijman · 2011
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Universality, characteristic kernels and rkhs embedding of measures
B. K. Sriperumbudur, K. Fukumizu, and G. R. Lanckriet · 2011
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Noxa, a sensor of proteasome integrity, is degraded by 26s proteasomes by an ubiquitin-independent pathway that is blocked by mcl-1
A. Craxton, M. Butterworth, N. Harper, L. Fairall, J. Schwabe, A. Ciechanover, and G. M. Cohen · 2012
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A kernel two-sample test
A. Gretton, K. M. Borgwardt, M. J. Rasch, B. Schölkopf, and A. Smola · 2012
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Determination of synthetic lethal interactions in kras oncogene-dependent cancer cells reveals novel therapeutic targeting strategies
M. Steckel, M. Molina-Arcas, B. Weigelt, M. Marani, P. H. Warne, H. Kuznetsov, G. Kelly, B. Saunders, M. Howell, J. Downward, and D. C. Hancock · 2012
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Active matrix completion
S. Chakraborty, J. Zhou, V. Balasubramanian, S. Panchanathan, I. Davidson, and J. Ye · 2013
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Efficient estimation of word representations in vector space
T. Mikolov, K. Chen, G. Corrado, and J. Dean · 2013
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Automated variational inference in probabilistic programming
D. Wingate and T. Weber · 2013
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Generative adversarial nets
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014
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Bcl2 and related prosurvival proteins require bak1 and bax to affect autophagy
L. M. Lindqvist and D. L. Vaux · 2014
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Black box variational inference
R. Ranganath, S. Gerrish, and D. Blei · 2014
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On the decreasing power of kernel and distance based nonparametric hypothesis tests in high dimensions
A. Ramdas, S. J. Reddi, B. Póczos, A. Singh, and L. Wasserman · 2015
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Nature Protocols , 11(9):1757–1774, 2016
Cell painting, a high-content image-based assay for morphological profiling using multiplexed fluorescent dyes · 2016
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Unsupervised feature extraction by time-contrastive learning and nonlinear ica
A. Hyvarinen and H. Morioka · 2016
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An information-theoretic analysis of thompson sampling
D. Russo and B. Van Roy · 2016
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A review of modern computational algorithms for bayesian optimal design
E. G. Ryan, C. C. Drovandi, J. M. McGree, and A. N. Pettitt · 2016
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Synergistic drug combinations for cancer identified in a crispr screen for pairwise genetic interactions
K. Han, E. E. Jeng, G. T. Hess, D. W. Morgens, A. Li, and M. C. Bassik · 2017
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BCL-2 family proteins: changing partners in the dance towards death
J. Kale, E. J. Osterlund, and D. W. Andrews · 2017
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Adam: A method for stochastic optimization, 2017
D. P. Kingma and J. Ba · 2017
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Kernel mean embedding of distributions: A review and beyond
K. Muandet, K. Fukumizu, B. Sriperumbudur, B. Schölkopf, et al · 2017
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Proteasome expression and activity in cancer and cancer stem cells
I. A. Voutsadakis · 2017
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Mutual information neural estimation
M. I. Belghazi, A. Baratin, S. Rajeshwar, S. Ozair, Y. Bengio, A. Courville, and D. Hjelm · 2018
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JAX: composable transformations of Python+NumPy programs, 2018
J. Bradbury, R. Frostig, P. Hawkins, M. J. Johnson, C. Leary, D. Maclaurin, G. Necula, A. Paszke, J. VanderPlas, S. Wanderman-Milne, and Q. Zhang · 2018
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Regulation of proteasome assembly and activity in health and disease
Adaptive sampling for discovery
Z. Xu, E. Shim, A. Tewari, and P. Zimmerman · 2022
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Interventional causal representation learning
K. Ahuja, D. Mahajan, Y. Wang, and Y. Bengio · 2023
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Modelling cellular perturbations with the sparse additive mechanism shift variational autoencoder
M. Bereket and T. Karaletsos · 2023
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Learning linear causal representations from interventions under general nonlinear mixing, 2023
S. Buchholz, G. Rajendran, E. Rosenfeld, B. Aragam, B. Schölkopf, and P. Ravikumar · 2023
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Combined inhibition of bcl-2 and mcl-1 overcomes bax deficiency-mediated resistance of tp53-mutant acute myeloid leukemia to individual bh3 mimetics
B. Z. Carter, P. Y. Mak, W. Tao, E. Ayoub, L. B. Ostermann, X. Huang, S. Loghavi, S. Boettcher, Y. Nishida, V. Ruvolo, P. E. Hughes, P. K. Morrow, T. Haferlach, S. Kornblau, M. Muftuoglu, and M. Andreeff · 2023
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A. Rousseau and A. Bertolotti · 2018
Cited alongside, same era.
The scripps molecular screening center and translational research institute
P. Baillargeon, V. Fernandez-Vega, B. P. Sridharan, S. Brown, P. R. Griffin, H. Rosen, B. Cravatt, L. Scampavia, and T. P. Spicer · 2019
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Pyro: Deep universal probabilistic programming
E. Bingham, J. P. Chen, M. Jankowiak, F. Obermeyer, N. Pradhan, T. Karaletsos, R. Singh, P. A. Szerlip, P. Horsfall, and N. D. Goodman · 2019
Cited alongside, same era.
Corum: the comprehensive resource of mammalian protein complexes—2019
M. Giurgiu, J. Reinhard, B. Brauner, I. Dunger-Kaltenbach, G. Fobo, G. Frishman, C. Montrone, and A. Ruepp · 2019
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Learning deep representations by mutual information estimation and maximization
R. D. Hjelm, A. Fedorov, S. Lavoie-Marchildon, K. Grewal, P. Bachman, A. Trischler, and Y. Bengio · 2019
Cited alongside, same era.
Nonlinear ica using auxiliary variables and generalized contrastive learning
A. Hyvarinen, H. Sasaki, and R. Turner · 2019
Cited alongside, same era.
scgen predicts single-cell perturbation responses
M. Lotfollahi, F. A. Wolf, and F. J. Theis · 2019
Cited alongside, same era.
Jump cell painting dataset: morphological impact of 136,000 chemical and genetic perturbations
S. N. Chandrasekaran, J. Ackerman, E. Alix, D. M. Ando, J. Arevalo, M. Bennion, N. Boisseau, A. Borowa, J. D. Boyd, L. Brino, P. J. Byrne, H. Ceulemans, C. Ch’ng, B. A. Cimini, D.-A. Clevert, N. Deflaux, J. G. Doench, T. Dorval, R. Doyonnas, V. Dragone, O. Engkvist, P. W. Faloon, B. Fritchman, F. Fuchs, S. Garg, T. J. Gilbert, D. Glazer, D. Gnutt, A. Goodale, J. Grignard, J. Guenther, Y. Han, Z. Hanifehlou, S. Hariharan, D. Hernandez, S. R. Horman, G. Hormel, M. Huntley, I. Icke, M. Iida, C. B. Jacob, S. Jaensch, J. Khetan, M. Kost-Alimova, T. Krawiec, D. Kuhn, C.-H. Lardeau, A. Lembke, F. Lin, K. D. Little, K. R. Lofstrom, S. Lotfi, D. J. Logan, Y. Luo, F. Madoux, P. A. M. Zapata, B. A. Marion, G. Martin, N. J. McCarthy, L. Mervin, L. Miller, H. Mohamed, T. Monteverde, E. Mouchet, B. Nicke, A. Ogier, A.-L. Ong, M. Osterland, M. Otrocka, P. J. Peeters, J. Pilling, S. Prechtl, C. Qian, K. Rataj, D. E. Root, S. K. Sakata, S. Scrace, H. Shimizu, D. Simon, P. Sommer, C. Spruiell, I. Sumia, S. E. Swalley, H. Terauchi, A. Thibaudeau, A. Unruh, J. V. de Waeter, M. V. Dyck, C. van Staden, M. Warchoł, E. Weisbart, A. Weiss, N. Wiest-Daessle, G. Williams, S. Yu, B. Zapiec, M. Żyła, S. Singh, and A. E. Carpenter · 2023
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High throughput microscopy and single cell phenotypic image-based analysis in toxicology and drug discovery
S. Fabio, K. S. Pankaj, S. Kazem, M. Michela, L. Demetrio, and A. M. Michael · 2023
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Rxrx3: Phenomics map of biology
M. M. Fay, O. Kraus, M. Victors, L. Arumugam, K. Vuggumudi, J. Urbanik, K. Hansen, S. Celik, N. Cernek, G. Jagannathan, et al · 2023
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Sequential optimal experimental design of perturbation screens guided by multi-modal priors
K. Huang, R. Lopez, J.-C. Hutter, T. Kudo, A. Rios, and A. Regev · 2023
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Learning nonparametric latent causal graphs with unknown interventions
Y. Jiang and B. Aragam · 2023
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Masked autoencoders are scalable learners of cellular morphology
O. Kraus, K. Kenyon-Dean, S. Saberian, M. Fallah, P. McLean, J. Leung, V. Sharma, A. Khan, J. Balakrishnan, S. Celik, et al · 2023
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Learning causal representations of single cells via sparse mechanism shift modeling
R. Lopez, N. Tagasovska, S. Ra, K. Cho, J. Pritchard, and A. Regev · 2023
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Predicting cellular responses to complex perturbations in high-throughput screens
M. Lotfollahi, A. Klimovskaia Susmelj, C. De Donno, L. Hetzel, Y. Ji, I. L. Ibarra, S. R. Srivatsan, M. Naghipourfar, R. M. Daza, B. Martin, J. Shendure, J. L. McFaline-Figueroa, P. Boyeau, F. A. Wolf, N. Yakubova, S. Günnemann, C. Trapnell, D. Lopez-Paz, and F. J. Theis · 2023
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Discobax discovery of optimal intervention sets in genomic experiment design
C. Lyle, A. Mehrjou, P. Notin, A. Jesson, S. Bauer, Y. Gal, and P. Schwab · 2023
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Mass spectrometry-based high-throughput proteomics and its role in biomedical studies and systems biology
C. B. Messner, V. Demichev, Z. Wang, J. Hartl, G. Kustatscher, M. Mülleder, and M. Ralser · 2023
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Next-generation forward genetic screens: uniting high-throughput perturbations with single-cell analysis
J. A. Morris, J. S. Sun, and N. E. Sanjana · 2023
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Neural design for genetic perturbation experiments
A. Pacchiano, D. Wulsin, R. A. Barton, and L. Voloch · 2023
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Modern bayesian experimental design
T. Rainforth, A. Foster, D. R. Ivanova, and F. B. Smith · 2023
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Linear causal disentanglement via interventions
C. Squires, A. Seigal, S. S. Bhate, and C. Uhler · 2023
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Rxrx1: A dataset for evaluating experimental batch correction methods
M. Sypetkowski, M. Rezanejad, S. Saberian, O. Kraus, J. Urbanik, J. Taylor, B. Mabey, M. Victors, J. Yosinski, A. R. Sereshkeh, et al · 2023
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Concept algebra for (score-based) text-controlled generative models
Z. Wang, L. Gui, J. Negrea, and V. Veitch · 2023
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Microsnoop: A generalized tool for unbiased representation of diverse microscopy images
D. Xun, R. Wang, X. Zhang, and Y. Wang · 2023
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Identifiability guarantees for causal disentanglement from soft interventions
J. Zhang, K. Greenewald, C. Squires, A. Srivastava, K. Shanmugam, and C. Uhler · 2023
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Season combinatorial intervention predictions with salt & peper
T. Gaudelet, A. Del Vecchio, E. M. Carrami, J. Cudini, C.-A. Kapourani, C. Uhler, and L. Edwards · 2024
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The biological essence of synthetic lethality: Bringing new opportunities for cancer therapy
M. Ge, J. Luo, Y. Wu, G. Shen, and X. Kuang · 2024
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Score-based causal representation learning: Linear and general transformations, 2024
B. Varıcı, E. Acartürk, K. Shanmugam, A. Kumar, and A. Tajer · 2024
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Epigenetic targeting of mcl-1 is synthetically lethal with bcl-xl/bcl-2 inhibition in model systems of glioblastoma
E. Shang, T. T. T. Nguyen, C. Shu, M.-A. Westhoff, G. Karpel-Massler, and M. D. Siegelin · 2072
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