@book{Lamport:Book:1989,
 author = {Lamport, Leslie},
 title = {Latex: A Document Preparation System},
 year = {1986},
 isbn = {0-201-15790-X},
 publisher = {Addison-Wesley Longman Publishing Co., Inc.},
 address = {Boston, MA, USA},
}

@misc{Hinton:arXiv:2015:Distilling,
 title={Distilling the knowledge in a neural network},
 author={Hinton, Geoffrey and Vinyals, Oriol and Dean, Jeff},
 OPTeprinttype={arXiv},
 OPTeprint={1503.02531},
 howpublished={Eprint \href{http://arxiv.org/abs/1503.02531}{arXiv:1503.02531}},
 OPTurl={http://arxiv.org/abs/1503.02531},
 year=2015
}



@String(PAMI = {IEEE Trans. Pattern Anal. Mach. Intell.})
@String(IJCV = {Int. J. Comput. Vis.})
@String(CVPR= {IEEE Conf. Comput. Vis. Pattern Recog.})
@String(ICCV= {Int. Conf. Comput. Vis.})
@String(ECCV= {Eur. Conf. Comput. Vis.})
@String(NIPS= {Adv. Neural Inform. Process. Syst.})
@String(ICPR = {Int. Conf. Pattern Recog.})
@String(BMVC= {Brit. Mach. Vis. Conf.})
@String(TOG= {ACM Trans. Graph.})
@String(TIP  = {IEEE Trans. Image Process.})
@String(TVCG  = {IEEE Trans. Vis. Comput. Graph.})
@String(TMM  = {IEEE Trans. Multimedia})
@String(ACMMM= {ACM Int. Conf. Multimedia})
@String(ICME = {Int. Conf. Multimedia and Expo})
@String(ICASSP=	{ICASSP})
@String(ICIP = {IEEE Int. Conf. Image Process.})
@String(ACCV  = {ACCV})
@String(ICLR = {Int. Conf. Learn. Represent.})
@String(IJCAI = {IJCAI})
@String(PR   = {Pattern Recognition})
@String(AAAI = {AAAI})
@String(CVPRW= {IEEE Conf. Comput. Vis. Pattern Recog. Worksh.})
@String(CSVT = {IEEE Trans. Circuit Syst. Video Technol.})

@String(SPL	= {IEEE Sign. Process. Letters})
@String(VR   = {Vis. Res.})
@String(JOV	 = {J. Vis.})
@String(TVC  = {The Vis. Comput.})
@String(JCST  = {J. Comput. Sci. Tech.})
@String(CGF  = {Comput. Graph. Forum})
@String(CVM = {Computational Visual Media})


@String(PAMI  = {IEEE TPAMI})
@String(IJCV  = {IJCV})
@String(CVPR  = {CVPR})
@String(ICCV  = {ICCV})
@String(ECCV  = {ECCV})
@String(NIPS  = {NeurIPS})
@String(ICPR  = {ICPR})
@String(BMVC  =	{BMVC})
@String(TOG   = {ACM TOG})
@String(TIP   = {IEEE TIP})
@String(TVCG  = {IEEE TVCG})
@String(TCSVT = {IEEE TCSVT})
@String(TMM   =	{IEEE TMM})
@String(ACMMM = {ACM MM})
@String(ICME  =	{ICME})
@String(ICASSP=	{ICASSP})
@String(ICIP  = {ICIP})
@String(ACCV  = {ACCV})
@String(ICLR  = {ICLR})
@String(IJCAI = {IJCAI})
@String(PR = {PR})
@String(AAAI = {AAAI})
@String(CVPRW= {CVPRW})
@String(CSVT = {IEEE TCSVT})


%%  datasets
@article{bock2022high,
  title={High-content CRISPR screening},
  author={Bock, Christoph and Datlinger, Paul and Chardon, Florence and Coelho, Matthew A and Dong, Matthew B and Lawson, Keith A and Lu, Tian and Maroc, Laetitia and Norman, Thomas M and Song, Bicna and others},
  journal={Nature Reviews Methods Primers},
  volume={2},
  number={1},
  pages={1--23},
  year={2022},
  publisher={Nature Publishing Group}
}
@article{ye2018drug,
  title={DRUG-seq for miniaturized high-throughput transcriptome profiling in drug discovery},
  author={Ye, Chaoyang and Ho, Daniel J and Neri, Marilisa and Yang, Chian and Kulkarni, Tripti and Randhawa, Ranjit and Henault, Martin and Mostacci, Nadezda and Farmer, Pierre and Renner, Steffen and others},
  journal={Nature communications},
  volume={9},
  number={1},
  pages={4307},
  year={2018},
  publisher={Nature Publishing Group UK London}
}
@article{dixit2016perturb,
  title={Perturb-Seq: dissecting molecular circuits with scalable single-cell RNA profiling of pooled genetic screens},
  author={Dixit, Atray and Parnas, Oren and Li, Biyu and Chen, Jenny and Fulco, Charles P and Jerby-Arnon, Livnat and Marjanovic, Nemanja D and Dionne, Danielle and Burks, Tyler and Raychowdhury, Raktima and others},
  journal={cell},
  volume={167},
  number={7},
  pages={1853--1866},
  year={2016},
  publisher={Elsevier}
}
% HUVEC 
@article{baudin2007protocol,
  title={A protocol for isolation and culture of human umbilical vein endothelial cells},
  author={Baudin, Bruno and Bruneel, Arnaud and Bosselut, Nelly and Vaubourdolle, Michel},
  journal={Nature protocols},
  volume={2},
  number={3},
  pages={481--485},
  year={2007},
  publisher={Nature Publishing Group UK London}
}

% cell paint
@article{bray2016cell,
  title={Cell Painting, a high-content image-based assay for morphological profiling using multiplexed fluorescent dyes},
  author={Bray, Mark-Anthony and Singh, Shantanu and Han, Han and Davis, Chadwick T and Borgeson, Blake and Hartland, Cathy and Kost-Alimova, Maria and Gustafsdottir, Sigrun M and Gibson, Christopher C and Carpenter, Anne E},
  journal={Nature protocols},
  volume={11},
  number={9},
  pages={1757--1774},
  year={2016},
  publisher={Nature Publishing Group UK London}
}

@article{yosef2023irfl,
  title={Irfl: Image recognition of figurative language},
  author={Yosef, Ron and Bitton, Yonatan and Shahaf, Dafna},
  journal={arXiv preprint arXiv:2303.15445},
  year={2023}
}

@article{cui2022spatially,
  title={Spatially restricted drivers and transitional cell populations cooperate with the microenvironment in untreated and chemo-resistant pancreatic cancer},
  author={Zhou, Daniel and Jayasinghe, Reyka G and Chen, Siqi and Herndon, John M and Iglesia, Michael D and Navale, Pooja and Wendl, Michael C and Caravan, Wagma and Sato, Kazuhito and Storrs, Erik and others},
  journal={Nature genetics},
  volume={54},
  number={9},
  pages={1390--1405},
  year={2022},
  publisher={Nature Publishing Group US New York}
}

@inproceedings{kraus2024masked,
  title={Masked Autoencoders for Microscopy are Scalable Learners of Cellular Biology},
  author={Kraus, Oren and Kenyon-Dean, Kian and Saberian, Saber and Fallah, Maryam and McLean, Peter and Leung, Jess and Sharma, Vasudev and Khan, Ayla and Balakrishnan, Jia and Celik, Safiye and others},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={11757--11768},
  year={2024}
}





%% SSL

@inproceedings{radford2021learning,
  title={Learning transferable visual models from natural language supervision},
  author={Radford, Alec and Kim, Jong Wook and Hallacy, Chris and Ramesh, Aditya and Goh, Gabriel and Agarwal, Sandhini and Sastry, Girish and Askell, Amanda and Mishkin, Pamela and Clark, Jack and others},
  booktitle={International conference on machine learning},
  pages={8748--8763},
  year={2021},
  organization={PMLR}
}

@inproceedings{hertz2023prompttoprompt,
title={Prompt-to-Prompt Image Editing with Cross-Attention Control},
author={Amir Hertz and Ron Mokady and Jay Tenenbaum and Kfir Aberman and Yael Pritch and Daniel Cohen-or},
booktitle={The Eleventh International Conference on Learning Representations },
year={2023},
url={https://openreview.net/forum?id=_CDixzkzeyb}
}

@article{ramesh2022hierarchical,
  title={Hierarchical text-conditional image generation with clip latents},
  author={Ramesh, Aditya and Dhariwal, Prafulla and Nichol, Alex and Chu, Casey and Chen, Mark},
  journal={arXiv preprint arXiv:2204.06125},
  volume={1},
  number={2},
  pages={3},
  year={2022}
}

@inproceedings{rombach2022high,
  title={High-resolution image synthesis with latent diffusion models},
  author={Rombach, Robin and Blattmann, Andreas and Lorenz, Dominik and Esser, Patrick and Ommer, Bj{\"o}rn},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={10684--10695},
  year={2022}
}

@misc{bunne2024buildvirtualcellartificial,
      title={How to Build the Virtual Cell with Artificial Intelligence: Priorities and Opportunities}, 
      author={Charlotte Bunne and Yusuf Roohani and Yanay Rosen and Ankit Gupta and Xikun Zhang and Marcel Roed and Theo Alexandrov and Mohammed AlQuraishi and Patricia Brennan and Daniel B. Burkhardt and Andrea Califano and Jonah Cool and Abby F. Dernburg and Kirsty Ewing and Emily B. Fox and Matthias Haury and Amy E. Herr and Eric Horvitz and Patrick D. Hsu and Viren Jain and Gregory R. Johnson and Thomas Kalil and David R. Kelley and Shana O. Kelley and Anna Kreshuk and Tim Mitchison and Stephani Otte and Jay Shendure and Nicholas J. Sofroniew and Fabian Theis and Christina V. Theodoris and Srigokul Upadhyayula and Marc Valer and Bo Wang and Eric Xing and Serena Yeung-Levy and Marinka Zitnik and Theofanis Karaletsos and Aviv Regev and Emma Lundberg and Jure Leskovec and Stephen R. Quake},
      year={2024},
      eprint={2409.11654},
      archivePrefix={arXiv},
      primaryClass={q-bio.QM},
      url={https://arxiv.org/abs/2409.11654}, 
}

@inproceedings{gutmann2010noise,
  title={Noise-contrastive estimation: A new estimation principle for unnormalized statistical models},
  author={Gutmann, Michael and Hyv{\"a}rinen, Aapo},
  booktitle={Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics},
  pages={297--304},
  year={2010},
}

@article{oord2018representation,
  title={Representation learning with contrastive predictive coding},
  author={Oord, Aaron van den and Li, Yazhe and Vinyals, Oriol},
  journal={arXiv preprint arXiv:1807.03748},
  year={2018}
}

@inproceedings{wang2024removing,
title={Removing Biases from Molecular Representations via Information Maximization},
author={Chenyu Wang and Sharut Gupta and Caroline Uhler and Tommi S. Jaakkola},
booktitle={The Twelfth International Conference on Learning Representations},
year={2024},
url={https://openreview.net/forum?id=7TOs9gjAg1}
}

@article{khosla2020supervised,
  title={Supervised contrastive learning},
  author={Khosla, Prannay and Teterwak, Piotr and Wang, Chen and Sarna, Aaron and Tian, Yonglong and Isola, Phillip and Maschinot, Aaron and Liu, Ce and Krishnan, Dilip},
  journal={Advances in Neural Information Processing Systems},
  volume={33},
  pages={18661--18673},
  year={2020}
}

@article{liang2024factorized,
  title={Factorized contrastive learning: Going beyond multi-view redundancy},
  author={Liang, Paul Pu and Deng, Zihao and Ma, Martin Q and Zou, James Y and Morency, Louis-Philippe and Salakhutdinov, Ruslan},
  journal={Advances in Neural Information Processing Systems},
  volume={36},
  year={2024}
}

@inproceedings{chen2020simple,
  title={A simple framework for contrastive learning of visual representations},
  author={Chen, Ting and Kornblith, Simon and Norouzi, Mohammad and Hinton, Geoffrey},
  booktitle={International Conference on Machine Learning},
  pages={1597--1607},
  year={2020},
}


@inproceedings{zheng2021weakly,
  title={Weakly supervised contrastive learning},
  author={Zheng, Mingkai and Wang, Fei and You, Shan and Qian, Chen and Zhang, Changshui and Wang, Xiaogang and Xu, Chang},
  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
  pages={10042--10051},
  year={2021}
}

@article{alwassel2020self,
  title={Self-supervised learning by cross-modal audio-video clustering},
  author={Alwassel, Humam and Mahajan, Dhruv and Korbar, Bruno and Torresani, Lorenzo and Ghanem, Bernard and Tran, Du},
  journal={Advances in Neural Information Processing Systems},
  volume={33},
  pages={9758--9770},
  year={2020}
}


% unpaired metrics


% embeding foundation models
% article{kraus2023masked,
%  title={Masked autoencoders are scalable learners of cellular morphology},
%  author={Kraus, Oren and Kenyon-Dean, Kian and Saberian, Saber and Fallah, Maryam and McLean, Peter and Leung, Jess and Sharma, %Vasudev and Khan, Ayla and Balakrishnan, Jia and Celik, Safiye and others},
%  journal={arXiv preprint arXiv:2309.16064},
%  year={2023}
%}


%% datasets?
%rxrx3


@article{Celik2022,
    doi = {10.1371/journal.pcbi.1012463},
    author = {Celik, Safiye AND Hütter, Jan-Christian AND Carlos, Sandra Melo AND Lazar, Nathan H. AND Mohan, Rahul AND Tillinghast, Conor AND Biancalani, Tommaso AND Fay, Marta M. AND Earnshaw, Berton A. AND Haque, Imran S.},
    journal = {PLOS Computational Biology},
    publisher = {Public Library of Science},
    title = {Building, benchmarking, and exploring perturbative maps of transcriptional and morphological data},
    year = {2024},
    month = {10},
    volume = {20},
    url = {https://doi.org/10.1371/journal.pcbi.1012463},
    pages = {1-24},
    abstract = {The continued scaling of genetic perturbation technologies combined with high-dimensional assays such as cellular microscopy and RNA-sequencing has enabled genome-scale reverse-genetics experiments that go beyond single-endpoint measurements of growth or lethality. Datasets emerging from these experiments can be combined to construct perturbative "maps of biology", in which readouts from various manipulations (e.g., CRISPR-Cas9 knockout, CRISPRi knockdown, compound treatment) are placed in unified, relatable embedding spaces allowing for the generation of genome-scale sets of pairwise comparisons. These maps of biology capture known biological relationships and uncover new associations which can be used for downstream discovery tasks. Construction of these maps involves many technical choices in both experimental and computational protocols, motivating the design of benchmark procedures to evaluate map quality in a systematic, unbiased manner. Here, we (1) establish a standardized terminology for the steps involved in perturbative map building, (2) introduce key classes of benchmarks to assess the quality of such maps, (3) construct 18 maps from four genome-scale datasets employing different cell types, perturbation technologies, and data readout modalities, (4) generate benchmark metrics for the constructed maps and investigate the reasons for performance variations, and (5) demonstrate utility of these maps to discover new biology by suggesting roles for two largely uncharacterized genes.},
    number = {10},

}


@article{fay2023rxrx3,
  title={Rxrx3: Phenomics map of biology},
  author={Fay, Marta M and Kraus, Oren and Victors, Mason and Arumugam, Lakshmanan and Vuggumudi, Kamal and Urbanik, John and Hansen, Kyle and Celik, Safiye and Cernek, Nico and Jagannathan, Ganesh and others},
  journal={Biorxiv},
  pages={2023--02},
  year={2023},
  publisher={Cold Spring Harbor Laboratory}
}

@article{moshkov2023predicting,
  title={Predicting compound activity from phenotypic profiles and chemical structures},
  author={Moshkov, Nikita and Becker, Tim and Yang, Kevin and Horvath, Peter and Dancik, Vlado and Wagner, Bridget K and Clemons, Paul A and Singh, Shantanu and Carpenter, Anne E and Caicedo, Juan C},
  journal={Nature Communications},
  volume={14},
  number={1},
  pages={1967},
  year={2023},
  publisher={Nature Publishing Group UK London}
}



%% matching
%% causal
@article{rubin1974estimating,
  title={Estimating causal effects of treatments in randomized and nonrandomized studies.},
  author={Rubin, Donald B},
  journal={Journal of educational Psychology},
  volume={66},
  number={5},
  pages={688},
  year={1974},
  publisher={American Psychological Association}
}

@article{sturma2024unpaired,
  title={Unpaired multi-domain causal representation learning},
  author={Sturma, Nils and Squires, Chandler and Drton, Mathias and Uhler, Caroline},
  journal={Advances in Neural Information Processing Systems},
  volume={36},
  year={2024}
}

@inproceedings{xi2024propensity,
  title={Propensity Score Alignment of Unpaired Multimodal Data},
  author={Xi, Johnny and Osea, Jana and Xu, Zuheng and Hartford, Jason},
  booktitle={Advances in Neural Information Processing Systems},
  year={2024}
}

@article{ryu2024cross,
  title={Cross-modality Matching and Prediction of Perturbation Responses with Labeled Gromov-Wasserstein Optimal Transport},
  author={Ryu, Jayoung and Lopez, Romain and Bunne, Charlotte and Regev, Aviv},
  journal={arXiv preprint arXiv:2405.00838},
  year={2024}
}


@article{tu2022cross,
  title={Cross-linked unified embedding for cross-modality representation learning},
  author={Tu, Xinming and Cao, Zhi-Jie and Mostafavi, Sara and Gao, Ge and others},
  journal={Advances in Neural Information Processing Systems},
  volume={35},
  pages={15942--15955},
  year={2022}
}


@article{lamiable2023revealing,
  title={Revealing invisible cell phenotypes with conditional generative modeling},
  author={Lamiable, Alexis and Champetier, Tiphaine and Leonardi, Francesco and Cohen, Ethan and Sommer, Peter and Hardy, David and Argy, Nicolas and Massougbodji, Achille and Del Nery, Elaine and Cottrell, Gilles and others},
  journal={Nature Communications},
  volume={14},
  number={1},
  pages={6386},
  year={2023},
  publisher={Nature Publishing Group UK London}
}
@article{way2023evolution,
  title={Evolution and impact of high content imaging},
  author={Way, Gregory P and Sailem, Heba and Shave, Steven and Kasprowicz, Richard and Carragher, Neil O},
  journal={Slas Discovery},
  volume={28},
  number={7},
  pages={292--305},
  year={2023},
  publisher={Elsevier}
}


@article{larsson2021spatially,
  title={Spatially resolved transcriptomics adds a new dimension to genomics},
  author={Larsson, Ludvig and Fris{\'e}n, Jonas and Lundeberg, Joakim},
  journal={Nature methods},
  volume={18},
  number={1},
  pages={15--18},
  year={2021},
  publisher={Nature Publishing Group US New York}
}


@article{stoeckius2017simultaneous,
  title={Simultaneous epitope and transcriptome measurement in single cells},
  author={Stoeckius, Marlon and Hafemeister, Christoph and Stephenson, William and Houck-Loomis, Brian and Chattopadhyay, Pratip K and Swerdlow, Harold and Satija, Rahul and Smibert, Peter},
  journal={Nature methods},
  volume={14},
  number={9},
  pages={865--868},
  year={2017},
  publisher={Nature Publishing Group}
}

@article{baek2020single,
  title={Single-cell ATAC sequencing analysis: from data preprocessing to hypothesis generation},
  author={Baek, Seungbyn and Lee, Insuk},
  journal={Computational and structural biotechnology journal},
  volume={18},
  pages={1429--1439},
  year={2020},
  publisher={Elsevier}
}

@article{sikkema2022integrated,
  title={An integrated cell atlas of the human lung in health and disease},
  author={Sikkema, Lisa and Strobl, D and Zappia, Luke and Madissoon, Elo and Markov, Nikolay S and Zaragosi, L and Ansari, Meshal and Arguel, M and Apperloo, Leonie and Becavin, Christophe and others},
  journal={BioRxiv},
  pages={2022--03},
  year={2022},
  publisher={Cold Spring Harbor Laboratory}
}

@article{krentzel2023deep,
  title={Deep learning in image-based phenotypic drug discovery},
  author={Krentzel, Daniel and Shorte, Spencer L and Zimmer, Christophe},
  journal={Trends in Cell Biology},
  volume={33},
  number={7},
  pages={538--554},
  year={2023},
  publisher={Elsevier}
}

@article{perlman2004multidimensional,
  title={Multidimensional drug profiling by automated microscopy},
  author={Perlman, Zachary E and Slack, Michael D and Feng, Yan and Mitchison, Timothy J and Wu, Lani F and Altschuler, Steven J},
  journal={Science},
  volume={306},
  number={5699},
  pages={1194--1198},
  year={2004},
  publisher={American Association for the Advancement of Science}
}


@article{heumos2023best,
  title={Best practices for single-cell analysis across modalities},
  author={Heumos, Lukas and Schaar, Anna C and Lance, Christopher and Litinetskaya, Anastasia and Drost, Felix and Zappia, Luke and L{\"u}cken, Malte D and Strobl, Daniel C and Henao, Juan and Curion, Fabiola and others},
  journal={Nature Reviews Genetics},
  volume={24},
  number={8},
  pages={550--572},
  year={2023},
  publisher={Nature Publishing Group UK London}
}


@article{boutros2015microscopy,
  title={Microscopy-based high-content screening},
  author={Boutros, Michael and Heigwer, Florian and Laufer, Christina},
  journal={Cell},
  volume={163},
  number={6},
  pages={1314--1325},
  year={2015},
  publisher={Elsevier}
}

@article{yang2022contrastive,
  title={Contrastive learning enables rapid mapping to multimodal single-cell atlas of multimillion scale},
  author={Yang, Meng and Yang, Yueyuxiao and Xie, Chenxi and Ni, Ming and Liu, Jian and Yang, Huanming and Mu, Feng and Wang, Jian},
  journal={Nature Machine Intelligence},
  volume={4},
  number={8},
  pages={696--709},
  year={2022},
  publisher={Nature Publishing Group UK London}
}

@article{bao2022integrative,
  title={Integrative spatial analysis of cell morphologies and transcriptional states with MUSE},
  author={Bao, Feng and Deng, Yue and Wan, Sen and Shen, Susan Q and Wang, Bo and Dai, Qionghai and Altschuler, Steven J and Wu, Lani F},
  journal={Nature biotechnology},
  volume={40},
  number={8},
  pages={1200--1209},
  year={2022},
  publisher={Nature Publishing Group US New York}
}

@article{fradkin2024molecules,
  title={How Molecules Impact Cells: Unlocking Contrastive PhenoMolecular Retrieval},
  author={Fradkin, Philip and Azadi, Puria and Suri, Karush and Wenkel, Frederik and Bashashati, Ali and Sypetkowski, Maciej and Beaini, Dominique},
  journal={arXiv preprint arXiv:2409.08302},
  year={2024}
}

@article{min2024multimodal,
  title={Multimodal contrastive learning for spatial gene expression prediction using histology images},
  author={Min, Wenwen and Shi, Zhiceng and Zhang, Jun and Wan, Jun and Wang, Changmiao},
  journal={Briefings in Bioinformatics},
  volume={25},
  number={6},
  pages={bbae551},
  year={2024},
  publisher={Oxford University Press}
}

@article{zhang2022multimodal,
  title={Multimodal single-cell translation and alignment with semi-supervised learning},
  author={Zhang, Ran and Meng-Papaxanthos, Laetitia and Vert, Jean-philippe and Noble, William Stafford},
  journal={Journal of Computational Biology},
  volume={29},
  number={11},
  pages={1198--1212},
  year={2022},
  publisher={Mary Ann Liebert, Inc., publishers 140 Huguenot Street, 3rd Floor New~…}
}

@article{zhu2023robust,
  title={Robust single-cell matching and multimodal analysis using shared and distinct features},
  author={Zhu, Bokai and Chen, Shuxiao and Bai, Yunhao and Chen, Han and Liao, Guanrui and Mukherjee, Nilanjan and Vazquez, Gustavo and McIlwain, David R and Tzankov, Alexandar and Lee, Ivan T and others},
  journal={Nature Methods},
  volume={20},
  number={2},
  pages={304--315},
  year={2023},
  publisher={Nature Publishing Group US New York}
}


@article{cao2022multi,
  title={Multi-omics single-cell data integration and regulatory inference with graph-linked embedding},
  author={Cao, Zhi-Jie and Gao, Ge},
  journal={Nature Biotechnology},
  volume={40},
  number={10},
  pages={1458--1466},
  year={2022},
  publisher={Nature Publishing Group US New York}
}



% embedders
@article{dosovitskiy2020image,
  title={An image is worth 16x16 words: Transformers for image recognition at scale},
  author={Dosovitskiy, Alexey},
  journal={arXiv preprint arXiv:2010.11929},
  year={2020}
}
@article{lee2024nv,
  title={NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models},
  author={Lee, Chankyu and Roy, Rajarshi and Xu, Mengyao and Raiman, Jonathan and Shoeybi, Mohammad and Catanzaro, Bryan and Ping, Wei},
  journal={arXiv preprint arXiv:2405.17428},
  year={2024}
}
@article{chen2024uni,
  title={Towards a General-Purpose Foundation Model for Computational Pathology},
  author={Chen, Richard J and Ding, Tong and Lu, Ming Y and Williamson, Drew FK and Jaume, Guillaume and Chen, Bowen and Zhang, Andrew and Shao, Daniel and Song, Andrew H and Shaban, Muhammad and others},
  journal={Nature Medicine},
  publisher={Nature Publishing Group},
  year={2024}
}
@article{lopez2018deep,
  title={Deep generative modeling for single-cell transcriptomics},
  author={Lopez, Romain and Regier, Jeffrey and Cole, Michael B and Jordan, Michael I and Yosef, Nir},
  journal={Nature methods},
  volume={15},
  number={12},
  pages={1053--1058},
  year={2018},
  publisher={Nature Publishing Group US New York}
}


@article{stuart2019comprehensive,
  title={Comprehensive integration of single-cell data},
  author={Stuart, Tim and Butler, Andrew and Hoffman, Paul and Hafemeister, Christoph and Papalexi, Efthymia and Mauck, William M and Hao, Yuhan and Stoeckius, Marlon and Smibert, Peter and Satija, Rahul},
  journal={cell},
  volume={177},
  number={7},
  pages={1888--1902},
  year={2019},
  publisher={Elsevier}
}

@article{liu2020jointly,
  title={Jointly defining cell types from multiple single-cell datasets using LIGER},
  author={Liu, Jialin and Gao, Chao and Sodicoff, Joshua and Kozareva, Velina and Macosko, Evan Z and Welch, Joshua D},
  journal={Nature protocols},
  volume={15},
  number={11},
  pages={3632--3662},
  year={2020},
  publisher={Nature Publishing Group UK London}
}

@article{hao2021integrated,
  title={Integrated analysis of multimodal single-cell data},
  author={Hao, Yuhan and Hao, Stephanie and Andersen-Nissen, Erica and Mauck, William M and Zheng, Shiwei and Butler, Andrew and Lee, Maddie J and Wilk, Aaron J and Darby, Charlotte and Zager, Michael and others},
  journal={Cell},
  volume={184},
  number={13},
  pages={3573--3587},
  year={2021},
  publisher={Elsevier}
}

@article{iorio2016landscape,
  title={A landscape of pharmacogenomic interactions in cancer},
  author={Iorio, Francesco and Knijnenburg, Theo A and Vis, Daniel J and Bignell, Graham R and Menden, Michael P and Schubert, Michael and Aben, Nanne and Gon{\c{c}}alves, Emanuel and Barthorpe, Syd and Lightfoot, Howard and others},
  journal={Cell},
  volume={166},
  number={3},
  pages={740--754},
  year={2016},
  publisher={Elsevier}
}


@inproceedings{zhu2017unpaired,
  title={Unpaired image-to-image translation using cycle-consistent adversarial networks},
  author={Zhu, Jun-Yan and Park, Taesung and Isola, Phillip and Efros, Alexei A},
  booktitle={Proceedings of the IEEE international conference on computer vision},
  pages={2223--2232},
  year={2017}
}

@article{liu2017unsupervised,
  title={Unsupervised image-to-image translation networks},
  author={Liu, Ming-Yu and Breuel, Thomas and Kautz, Jan},
  journal={Advances in neural information processing systems},
  volume={30},
  year={2017}
}

@inproceedings{almahairi2018augmented,
  title={Augmented cyclegan: Learning many-to-many mappings from unpaired data},
  author={Almahairi, Amjad and Rajeshwar, Sai and Sordoni, Alessandro and Bachman, Philip and Courville, Aaron},
  booktitle={International conference on machine learning},
  pages={195--204},
  year={2018},
  organization={PMLR}
}


@inproceedings{amodio2018magan,
  title={MAGAN: Aligning biological manifolds},
  author={Amodio, Matthew and Krishnaswamy, Smita},
  booktitle={International conference on machine learning},
  pages={215--223},
  year={2018},
  organization={PMLR}
}


@article{yang2021multi,
  title={Multi-domain translation between single-cell imaging and sequencing data using autoencoders},
  author={Yang, Karren Dai and Belyaeva, Anastasiya and Venkatachalapathy, Saradha and Damodaran, Karthik and Katcoff, Abigail and Radhakrishnan, Adityanarayanan and Shivashankar, GV and Uhler, Caroline},
  journal={Nature communications},
  volume={12},
  number={1},
  pages={31},
  year={2021},
  publisher={Nature Publishing Group UK London}
}

@inproceedings{nakada2023understanding,
  title={Understanding multimodal contrastive learning and incorporating unpaired data},
  author={Nakada, Ryumei and Gulluk, Halil Ibrahim and Deng, Zhun and Ji, Wenlong and Zou, James and Zhang, Linjun},
  booktitle={International Conference on Artificial Intelligence and Statistics},
  pages={4348--4380},
  year={2023},
  organization={PMLR}
}

@article{kawakita2024gromov,
  title={Gromov--Wasserstein unsupervised alignment reveals structural correspondences between the color similarity structures of humans and large language models},
  author={Kawakita, Genji and Zeleznikow-Johnston, Ariel and Tsuchiya, Naotsugu and Oizumi, Masafumi},
  journal={Scientific Reports},
  volume={14},
  number={1},
  pages={15917},
  year={2024},
  publisher={Nature Publishing Group UK London}
}

@inproceedings{park2020contrastive,
  title={Contrastive learning for unpaired image-to-image translation},
  author={Park, Taesung and Efros, Alexei A and Zhang, Richard and Zhu, Jun-Yan},
  booktitle={Computer Vision--ECCV 2020: 16th European Conference, Glasgow, UK, August 23--28, 2020, Proceedings, Part IX 16},
  pages={319--345},
  year={2020},
  organization={Springer}
}


@article{kriebel2022uinmf,
  title={UINMF performs mosaic integration of single-cell multi-omic datasets using nonnegative matrix factorization},
  author={Kriebel, April R and Welch, Joshua D},
  journal={Nature communications},
  volume={13},
  number={1},
  pages={780},
  year={2022},
  publisher={Nature Publishing Group UK London}
}

@article{gao2020ucmh,
  title={UCMH: Unpaired cross-modal hashing with matrix factorization},
  author={Gao, Jing and Zhang, Wenjun and Zhong, Fangming and Chen, Zhikui},
  journal={Neurocomputing},
  volume={418},
  pages={178--190},
  year={2020},
  publisher={Elsevier}
}

@article{demetci2022scot,
  title={SCOT: single-cell multi-omics alignment with optimal transport},
  author={Demetci, Pinar and Santorella, Rebecca and Sandstede, Bj{\"o}rn and Noble, William Stafford and Singh, Ritambhara},
  journal={Journal of computational biology},
  volume={29},
  number={1},
  pages={3--18},
  year={2022},
  publisher={Mary Ann Liebert, Inc., publishers 140 Huguenot Street, 3rd Floor New~…}
}


@article{tsai2022learning,
  title={Learning weakly-supervised contrastive representations},
  author={Tsai, Yao-Hung Hubert and Li, Tianqin and Liu, Weixin and Liao, Peiyuan and Salakhutdinov, Ruslan and Morency, Louis-Philippe},
  journal={arXiv preprint arXiv:2202.06670},
  year={2022}
}


@article{bendidi2024benchmarking,
  title={Benchmarking Transcriptomics Foundation Models for Perturbation Analysis: one PCA still rules them all},
  author={Bendidi, Ihab and Whitfield, Shawn and Kenyon-Dean, Kian and Yedder, Hanene Ben and Mesbahi, Yassir El and Noutahi, Emmanuel and Denton, Alisandra K},
  journal={arXiv preprint arXiv:2410.13956},
  year={2024}
}

@article{korsunsky2019fast,
  title={Fast, sensitive and accurate integration of single-cell data with Harmony},
  author={Korsunsky, Ilya and Millard, Nghia and Fan, Jean and Slowikowski, Kamil and Zhang, Fan and Wei, Kevin and Baglaenko, Yuriy and Brenner, Michael and Loh, Po-ru and Raychaudhuri, Soumya},
  journal={Nature methods},
  volume={16},
  number={12},
  pages={1289--1296},
  year={2019},
  publisher={Nature Publishing Group US New York}
}




@article{goh2017batch,
  title={Why batch effects matter in omics data, and how to avoid them},
  author={Goh, Wilson Wen Bin and Wang, Wei and Wong, Limsoon},
  journal={Trends in biotechnology},
  volume={35},
  number={6},
  pages={498--507},
  year={2017},
  publisher={Elsevier}
}


@article{ballard2024deep,
  title={Deep learning-based approaches for multi-omics data integration and analysis},
  author={Ballard, Jenna L and Wang, Zexuan and Li, Wenrui and Shen, Li and Long, Qi},
  journal={BioData Mining},
  volume={17},
  number={1},
  pages={38},
  year={2024},
  publisher={Springer}
}