Livak, Kenneth J.

Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2−ΔΔCT Method

Livak, K. J., & Schmittgen, T. D. (2001) · Methods

Molecular Biology Techniques and ApplicationsGene expression and cancer classification

Cited by 180,860

Analyzing real-time PCR data by the comparative CT method

Schmittgen, T. D., & Livak, K. J. (2008) · Nature Protocols

Molecular Biology Techniques and ApplicationsGene expression and cancer classification

Cited by 26,190

The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells

Trapnell, C., Cacchiarelli, D., Grimsby, J., Pokharel, P., Li, S., Morse, M., Lennon, N. J., Livak, K. J., Mikkelsen, T. S., & Rinn, J. L. (2014) · Nature Biotechnology

Single-cell and spatial transcriptomicsGene Regulatory Network Analysis

Cited by 7,314

Neoantigen vaccine generates intratumoral T cell responses in phase Ib glioblastoma trial

Keskin, D. B., Anandappa, A. J., Sun, J., Tirosh, I., Mathewson, N. D., Li, S., Oliveira, G., Giobbie-Hurder, A., Felt, K., Gjini, E., et al. (2019) · Nature

Cancer Immunotherapy and BiomarkersImmunotherapy and Immune Responses

Cited by 1,432

CEL-seq2: sensitive highly-multiplexed single-cell RNA-Seq

Hashimshony, T., Senderovich, N., Avital, G., Klochendler, A., de Leeuw, Y., Anavy, L., Gennert, D., Li, S., Livak, K. J., Rozenblatt-Rosen, O., et al. (2016) · Genome Biology

Single-cell and spatial transcriptomicsGenomics and Phylogenetic Studies

Cited by 1,125

Mitochondrial Reprogramming Underlies Resistance to BCL-2 Inhibition in Lymphoid Malignancies

Guièze, R., Liu, V. M., Rosebrock, D., Jourdain, A. A., Hernández-Sánchez, M., Martinez Zurita, A., Sun, J., Ten Hacken, E., Baranowski, K., Thompson, P. A., et al. (2019) · Cancer Cell

Cell death mechanisms and regulationChronic Lymphocytic Leukemia Research

Cited by 361

Clonal evolution in patients with chronic lymphocytic leukaemia developing resistance to BTK inhibition

Burger, J. A., Landau, D. A., Taylor-Weiner, A., Bozic, I., Zhang, H., Sarosiek, K., Wang, L., Stewart, C., Fan, J., Hoellenriegel, J., et al. (2016) · Nature Communications

Chronic Lymphocytic Leukemia ResearchLymphoma Diagnosis and Treatment

Cited by 345

Applying high-dimensional single-cell technologies to the analysis of cancer immunotherapy

Gohil, S. H., Iorgulescu, J. B., Braun, D. A., Keskin, D. B., & Livak, K. J. (2021) · Nature Reviews Clinical Oncology

Single-cell and spatial transcriptomicsCancer Immunotherapy and Biomarkers

Cited by 282

Taking qPCR to a higher level: analysis of CNV reveals the power of high throughput qPCR to enhance quantitative resolution

Weaver, S., Dube, S., Mir, A., Qin, J., Sun, G., Ramakrishnan, R., Jones, R. C., & Livak, K. J. (2010) · Methods

Molecular Biology Techniques and ApplicationsGenomic variations and chromosomal abnormalities

Cited by 220

Multiplexed, targeted profiling of single-cell proteomes and transcriptomes in a single reaction

Genshaft, A. S., Li, S., Gallant, C. J., Darmanis, S., Prakadan, S. M., Ziegler, C. G. K., Lundberg, M., Fredriksson, S., Hong, J., Regev, A., et al. (2016) · Genome Biology

Single-cell and spatial transcriptomicsAdvanced Proteomics Techniques and Applications

Cited by 175

A practical solution for preserving single cells for RNA sequencing

Attar, M., Sharma, E., Li, S., Bryer, C., Cubitt, L., Broxholme, J., Lockstone, H., Kinchen, J., Simmons, A., Piazza, P., et al. (2018) · Scientific Reports

Single-cell and spatial transcriptomicsMolecular Biology Techniques and Applications

Cited by 80