Liqian Ma

• Support drug discovery and development pipelines by leading indication selection and product differentiation strategy • Support decision-making on precision medicine by identifying response biomarkers and expanding targetable indications • Lead initiatives in cutting-edge genomic technology to derive biological insights

• Leveraged large clinical and molecular (genomic, transcriptomic) datasets for therapeutic target discovery and biomarker characterization using statistical modeling, data visualization and data interpretation • Presented high-impact findings to the senior leaders of biotech and pharma clients to facilitate the decision of clinical development • Provided intelligence support to sales and marketing • Selected Skills: Molecular data (RNA, DNA) analysis, clinical data cleaning and analysis, survival analysis, cloud computing

• PhD Thesis: 27-hydroxycholesterol promotes breast cancer metastasis through the modulation of myeloid immune cells • Investigated the 27-hydroxycholesterol-driven, myeloid cell-mediated immunosuppression and T cell dysfunction that contribute to tumor progression • Developed RNA sequencing analysis pipelines and foundational experimental protocols, such as primary immune cell culture/cocultures and setting up experiment for RNAseq/single-cell RNAseq, for the entire laboratory • Presented research work regularly in regional and national conferences, such as AACR and ENDO • Reviewed manuscripts submitted to peer-review journals • Mentored 4 undergraduate students, supervising them in experimental research and helping them contribute meaningfully to projects • Selected Skills: Mouse models, Primary/mammalian cell culture, Flow cytometry, ELISA, Immunofluorescence, in vivo bioluminescence imaging, qPCR, RNA sequencing analysis, Single-cell RNA sequencing analysis

• Led and worked in teams on three machine-learning projects with H3ABioNet, the bioinformatics infrastructure of the NIH-funded Human, Heredity, and Health in Africa consortium • Developed project proposals to use genotype information to predict disease outcome and managed project teams by organizing group meetings, assigning tasks and managing teamwork progress • Reviewed RNAseq node accredation reports • Independently analyzed RNAseq data for the research groups in the University of Illinois Urbana-Champaign as a part of HPCBio • Selected Skills: RNA sequencing analysis, Machine-learning and Cloud-computing

• Conducted literature review and establish work plan for pooled CRISPR screening with single-cell transcriptomic readout (CROP-seq) • Analyzed multi-omics datasets (REAP-Seq, Proteomics) to identify novel therapeutic targets by applying statistical modeling and machine-learning • Presented findings to academic collaborators and cross-functional team leaders • Led workshop to train team members on new RNA sequencing data analysis pipelines • Selected Skills: Single-cell RNA sequencing analysis, Proteomics data analysis, Gene/protein co-expression network analysis, Cloud-computing

Outstanding Thesis Award

Summa Cum Laude Honors in Biology