Journal papers

• A. Forrow and G. Schiebinger (2021). LineageOT is a unified framework for lineage tracing and trajectory inference. Nature Communications.

• G. Schiebinger (2021). Reconstructing developmental landscapes and trajectories from single-cell data. Current Opinion in Systems Biology.

• H. Lavenant, S. Zhang, Y.H. Kim and G. Schiebinger (2021). Towards a mathematical theory of trajectory inference. arXiv.

• S. Zhang, A. Afanassiev, L. Greenstreet, T. Matsumoto, G. Schiebinger (2021). Optimal transport analysis reveals trajectories in steady-state systems. bioRxiv.

• H Li, J Ezike, A Afanassiev, L Greenstreet, S Zhang, J Whangbo, V L. Butty, E Moiso, GG Connelly, V Morris, D Wang, GQ Daley, S Garg, ST Chou, A Regev, E Lummertz da Rocha, G Schiebinger, RG Rowe (2021). Hematopoiesis at single cell resolution spanning human development and maturation. bioRxiv.

• AJ Massri, L Greenstreet, A Afanassiev, A Berrio Escobar, GM Wray, G Schiebinger, DR McClay (2021). Developmental Single-cell transcriptomics in the Lytechinus variegatus 1 Sea Urchin Embryo. Development.

• AJ. Massri, G Schiebinger, A Berrio, L Wang, G Wray, D McClay (2020). Methodologies for Following EMT In Vivo at Single Cell Resolution. The Epithelial-to Mesenchymal Transition (chapter in book).

• G. Schiebinger*, J. Shu*, M. Tabaka*, B. Cleary*, V. Subramanian, J. Gould, A. Solomon, S. Liu, S. Lin, P. Berube, L. Lee, J. Chen, J. Brumbaugh, P. Rigollet, K. Hochedlinger, R. Jaenisch, A. Regev and E. Lander (2019). Reconstruction of developmental landscapes by optimal-transport analysis of single-cell gene expression sheds light on cellular reprogramming. Cell. (bioRxiv version posted 2017).

• N. Boyd, G. Schiebinger and B. Recht (2017). The Alternating Descent Conditional Gradient Method for Sparse Inverse Problems. SIAM Journal on Optimization. Our code is available here.

• G. Schiebinger, E. Robeva and B. Recht (2017). Superresolution without Separation. Information and Inference, Oxford University Press.

• G. Schiebinger, M. J. Wainwright and B. Yu (2015). The Geometry of Kernelized Spectral Clustering. Annals of Statistics. vol. 43, no. 2, pages 819-846.

• A. Guntuboyina, S. Saha and G. Schiebinger (2014). Sharp Inequalities for f-divergences. IEEE Transactions on Information Theory. vol. 60, pages 104-121.

• L. A. Warren, D. J. Rossi, G. Schiebinger, I. L. Weissman, S. K. Kim and S. R. Quake (2007). Transcriptional instability is not a universal attribute of aging. Aging Cell. vol. 6, pages 775-782.

Conference papers

• A. Forrow, J.C. Hutter, M. Nitzan, P. Rigollet, G. Schiebinger, and J. Weed. Statistical Optimal Transport via Factored Couplings. AISTATS 2019.

• M.E. Shiffman, W. Stephenson, G. Schiebinger, T. Campbell, J. Huggins, A. Regev, and T. Broderick. (2017). Probabilistic reconstruction of cellular differentiation trees from single-cell RNA-seq data. NIPS Workshop on Bayesian Computation.

• A short version of Superresolution without Separation appeared in CAMSAP 2015. (full version published in journal, see above).

• A short version of The Alternating Descent Conditional Gradient Method for Sparse Inverse Problems appeared in CAMSAP 2015. (full version published in journal, see above).