All Published

Decoding heterogeneous single-cell perturbation responses

87. Song, B., Liu, D., Dai, W., McMyn, N.F., Wang, Q., Yang, D., Krejci, A., Vasilyev, A., Untermoser, N., Loregger, A., Song, D., Williams, B., Rosen, B., Cheng, X., Chao, L., Kale, H.T., Zhang, H., Diao, Y., Bürckstümmer, T., Siliciano, J.D., Li, J.J., Siliciano, R.F., Huangfu, D., & Li, W. (2025). Decoding heterogeneous single-cell perturbation […]

Integrated molecular and functional characterization of the intrinsic apoptotic machinery identifies therapeutic vulnerabilities in malignant glioma

83. Fernandez, E.G., Mai, W.X., Song, K., Bayley, N.A., Kim, J., Zhu, H., Pioso, M., Young, P., Andrasz, C., Cadet, D., Liau, L.M., Li, G., Yong, W.H., Rodriguez, F., Dixon, S.J., Souers, A.J., Li, J.J., Graeber, T.G., Cloughesy, T.F. & Nathanson, D.A. (2024). Integrated molecular and functional characterization of the intrinsic apoptotic machinery identifies therapeutic […]

Response to “Neglecting normalization impact in semi-synthetic RNA-seq data simulation generates artificial false positives” and “Winsorization greatly reduces false positives by popular differential expression methods when analyzing human population samp

82. Ge, X.*, Li, Y.*, Li, W., and Li, J.J. (2024). Response to “Neglecting normalization impact in semi-synthetic RNA-seq data simulation generates artificial false positives” and “Winsorization greatly reduces false positives by popular differential expression methods when analyzing human population samples”. Genome Biology 25:283.