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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Learning interpretable cellular responses to complex perturbations in high-throughput screens
Mohammad Lotfollahi, Anna Klimovskaia Susmelj, Carlo De Donno, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2021)
Open Access | Times Cited: 48

Showing 26-50 of 48 citing articles:

Spatially resolved multiomics of human cardiac niches
Kazumasa Kanemaru, James Cranley, Daniele Muraro, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 6
Biologically informed deep learning to infer gene program activity in single cells
Mohammad Lotfollahi, Sergei Rybakov, Karin Hrovatin, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 10
MultiCPA: Multimodal Compositional Perturbation Autoencoder
Kemal İnecik, Andreas Uhlmann, Mohammad Lotfollahi, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 10
Fatecode: Cell fate regulator prediction using classification autoencoder perturbation
Mehrshad Sadria, Anita T. Layton, Sidharta Goyal, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 10
Mapping lineage-traced cells across time points with moslin
Marius Lange, Zoe Piran, Michal Klein, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 5
scFormer: A Universal Representation Learning Approach for Single-Cell Data Using Transformers
Haotian Cui, Xiaoming Wang, Hassaan Maan, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 9
Machine Learning Approaches to Single-Cell Data Integration and Translation
Caroline Uhler, G. V. Shivashankar
Proceedings of the IEEE (2022) Vol. 110, Iss. 5, pp. 557-576
Open Access | Times Cited: 8
Delineating the Effective Use of Self-Supervised Learning in Single-Cell Genomics
Till Richter, Mojtaba Bahrami, Yufan Xia, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 1
Causal identification of single-cell experimental perturbation effects with CINEMA-OT
Mingze Dong, Bao Wang, Jessica Wei, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 6
CellDrift: inferring perturbation responses in temporally sampled single-cell data
Kang Jin, Daniel Schnell, Guangyuan Li, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 5
Open Access | Times Cited: 6
Biological representation disentanglement of single-cell data
Zoe Piran, Niv Cohen, Yedid Hoshen, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 2
Inferring therapeutic vulnerability within tumors through integration of pan-cancer cell line and single-cell transcriptomic profiles
Weijie Zhang, Danielle Maeser, Adam F. Lee, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 2
A Cross-Modal Autoencoder Framework Learns Holistic Representations of Cardiovascular State
Adityanarayanan Radhakrishnan, Samuel Friedman, Shaan Khurshid, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 3
From single-omics to interactomics: How can ligand-induced perturbations modulate single-cell phenotypes?
Luiz F. Piochi, Alexandre Gaspar, Nícia Rosário‐Ferreira, et al.
Advances in protein chemistry and structural biology (2022), pp. 45-83
Closed Access | Times Cited: 3
Modeling CAR Response at the Single-Cell Level Using Conditional Optimal Transport
Alice Driessen, Jannis Born, Rocío Castellanos-Rueda, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
A deep generative framework with embedded vector arithmetic and classifier for sample generation, label transfer, and clustering of single-cell data
Lifei Wang, Rui Lin Nie, Zhang Zhang, et al.
Cell Reports Methods (2023) Vol. 3, Iss. 8, pp. 100558-100558
Open Access | Times Cited: 1
Biologically informed variational autoencoders allow predictive modeling of genetic and drug induced perturbations
Daria Doncevic, Carl Herrmann
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 2
Generative Modeling of Single Cell Gene Expression for Dose-Dependent Chemical Perturbations
Omar Kana, Rance Nault, David Filipovic, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 2
Extrapolating Heterogeneous Time-Series Gene Expression Data using Sagittarius
Addie Woicik, Mingxin Zhang, Janelle Chan, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 2
CellDrift: Inferring Perturbation Responses in Temporally-Sampled Single Cell Data
Kang Jin, Daniel Schnell, Guangyuan Li, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 1
Simple Causal Relationships in Gene Expression Discovered through Deep Learned Collective Variables
Ching-Hao Wang, Kalin Vetsigian, Chris Lin, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access
Disentangling gene expression burden identifies generalizable phenotypes induced by synthetic gene networks
Aqib Hasnain, Amin Espah Borujeni, Yongjin Park, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access
Designing Single Cell RNA-Sequencing Experiments for Learning Latent Representations
Martin Treppner, Stefan Haug, Anna Köttgen, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access
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