About

Andrea Califano is the Clyde and Helen Wu Professor of Chemical and Systems Biology in the Departments of Systems Biology, Biochemistry & Molecular Biophysics, Biomedical Informatics, and Medicine at Columbia University Irving Medical Center. He is also the founding chair of the Department of Systems Biology and serves as the director of the JP Sulzberger Columbia Genome Center, as well as co-leader of the Precision Oncology and Systems Biology Program at the Herbert Irving Comprehensive Cancer Institute. A physicist by training, Dr. Califano has pioneered the field of systems biology by developing innovative, systematic approaches to understand the molecular factors that lead to cancer progression and drug resistance at the single-cell level. His research emphasizes analyzing complex, tumor-specific molecular interaction networks to identify master regulator proteins that drive tumorigenesis and maintain tumor cell homeostasis, despite these regulators often not being mutated or differentially expressed. His lab combines computational and experimental methodologies to reconstruct cellular regulatory and signaling logic, discover small molecules and combinations that target master regulators, and translate these findings into clinical studies, including personalized N-of-1 trials. Dr. Califano's work has led to several clinical applications, such as targeted therapies in neuroendocrine tumors, breast cancer, pancreatic ductal carcinoma, and prostate cancer. His contributions to cancer research have been recognized through numerous awards and honors, including election to the National Academy of Medicine, and he actively participates in scientific advisory boards and editorial roles in the field.

Research topics

• Biology
• Genetics
• Computational biology
• Cancer research
• Medicine
• Cell biology
• Computer Science
• Internal medicine
• Pathology
• Political Science
• Oncology
• Immunology
• Biochemistry
• Neuroscience
• Bioinformatics
• Pharmacology

Selected publications

• Abstract 3084: Network-based discovery of tumor-checkpoint inverter drugs targeting pancreatic ductal adenocarcinoma cell states and macrophage reprogramming

  Cancer Research · 2026-04-03

  articleSenior author

  Abstract Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, driven by extreme tumor heterogeneity and a profoundly immunosuppressive tumor microenvironment (TME). Distinct PDAC cell states—Gastrointestinal-like (GLS), Morphogenic (MOS), and Primitive (PLS)—coexist within individual tumors and are further stratified by MAPK activity (M+/M-), reflecting dynamic transcriptional programs sustained by Master Regulator (MR) proteins. These cell states are hypothesized to differentially modulate the tumor-associated macrophages in the TME. To investigate this, we established a co-culture system of THP-1-derived macrophages with PDAC cell lines representing each state and profiled macrophage transcriptional reprogramming. Macrophages co-cultured with distinct PDAC states exhibited differential activation of M2-like and TREM2+/APOE+/C1Q+ immunosuppressive phenotype, suggesting that PDAC cell states may uniquely influence macrophage phenotypes and immune evasion. To identify compounds capable of reprogramming these malignant states, we applied a network-based systems biology framework integrating ARACNe and VIPER to infer MR activity across PDAC states, OncoMatch to identify representative cell line models, and OncoTreat to predict small molecules capable of inverting tumor checkpoint-module activity. Cross-model validation identified state-specific candidate drugs, including Leuprolide, Vinblastine, and Mercaptopurine for GLS; Vindesine, Gossypol, and Binimetinib for MOS; and AT9283, Crizotinib, and Afatinib for PLS. Predicted MR-inversion scores correlated with experimental dose-response profiles in cell lines selected via OncoMatch. Together, these results establish a mechanistic link between tumor-intrinsic transcriptional states and macrophage immunosuppression, while identifying mutation-agnostic, state-specific drugs capable of reprogramming both tumor and immune compartments. This work provides a generalizable framework for network-based drug repurposing to overcome transcriptional plasticity and immune resistance in PDAC. Citation Format: Yining Chen, Alvaro Curiel-Garcia, Alex Piacentini, Zhouzerui Liu, Tim Olsen, Richard Yau, Praveer Sharma, Liz Murray, Gaetano Viscido, Ken Olive, Andrea Califano. Network-based discovery of tumor-checkpoint inverter drugs targeting pancreatic ductal adenocarcinoma cell states and macrophage reprogramming [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 3084.

  PublisherDOI

• Abstract 4938: Elucidation and pharmacologic targeting of master regulator proteins representing mechanistic determinants of macrophage state and immunoevasive potential

  Cancer Research · 2026-04-03

  articleSenior author

  Abstract PURPOSE: Macrophages (mΦ) exhibit extensive transcriptional plasticity within the tumor microenvironment (TME). While M1 mΦ promote anti-tumor immunity, regulatory M2 mΦ drive tumor progression and resistance to immune checkpoint therapy. In a recent study, Obradovic et al. (Cell 2021) used VIPER, a network-based algorithm that infers protein activity from transcriptomic data, to identify a highly immunosuppressive TAM subset in clear cell renal carcinoma (ccRCC) characterized by TREM2+/C1Q+/APOE+ (TCA+) expression. TCA+ mΦ were associated with poor prognosis, metastasis, and immune evasion. We aim to identify Master Regulator (MR) proteins that mechanistically control the TCA+ program and may serve as actionable targets for selective depletion or reprogramming of these cells toward neutral, antitumor or pro-inflammatory states. METHODS: We performed pooled single-cell CRISPR interference (CRISPRi) via Perturb-seq targeting 50 candidate MRs identified by VIPER from genes differentially expressed in TCA+ versus M0/M1 mΦs, followed by time-resolved scRNA-seq. THP-1 monocytes were differentiated and polarized to the M2 state using IL-4 and IL-13 for 48 hours, then profiled across seven time points spanning M2 polarization (0, 6, 12, 24, 48, 96, 192 hr). Approximately 100,000 cells per time point were analyzed, along with ∼10,000 unperturbed THP-1-derived M0, M1, and M2 mΦs as references. We aim to generate perturbational RNA-seq profiles of TCA+ mΦs with >350 drugs using PLATE-seq to identify compounds that either target individual MRs (OncoTarget) or invert the global MR-activity signature (OncoTreat), thus phenocopying validated genetic perturbations. UNPUBLISHED DATA: We generated a comprehensive dataset comprising ∼700,000 time-resolved (∼100,000 cells per time point), genetically perturbed mΦs, enabling high-resolution characterization of MR-specific transcriptional responses across the full course of M2/TCA+ polarization. The dataset captures early, intermediate, and late transcriptional changes induced by targeted repression of candidate MRs, providing a dynamic view of the regulatory architecture underlying the acquisition and maintenance of the TCA+ state. We will integrate with >350 drug-perturbation profiles to establish a matched pharmacologic resource for downstream identification of compounds capable of modulating MR activity or globally shifting the TCA+ transcriptional program. CONCLUSION: This study provides a large-scale, time-resolved map of regulatory programs in immunosuppressive TCA+ mΦs, with the aim of identifying and targeting Master Regulators to invert their immunosuppressive phenotype. This framework offers a path to neutralize mΦ-mediated immunosuppression and improve responses to immune checkpoint therapy. Citation Format: Gaetano Viscido, Mikko Turunen, Zhouzerui Liu, Justyn Chang, Meghna S. Raman, Leo B. Dupire, Hanrui Zhang, Tim Olsen, Jeremy Worley, Aleksandar Obradovic, Andrea Califano. Elucidation and pharmacologic targeting of master regulator proteins representing mechanistic determinants of macrophage state and immunoevasive potential [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 4938.

  PublisherDOI

• Abstract A017: RAS inhibition and cytotoxic chemotherapy target complementary cell states in pancreatic cancer

  Cancer Research · 2026-03-05

  article

  Abstract Multiple studies have demonstrated preclinical activity of RAS inhibitors in models of pancreatic ductal adenocarcinoma (PDAC) and early results from ongoing clinical trials show promise. Following our earlier work using RMC-7977 (a preclinical tool compound related to the investigational RAS(ON) multi-selective inhibitor daraxonrasib) in a broad range of preclinical models, we elected to study the impact of RAS(ON) inhibition and standard-of-care (SOC) cytotoxic chemotherapies on the heterogeneity of malignant cells in PDAC. We performed single cell RNA sequencing (scRNAseq) on over three dozen PDAC tumors from the KPC genetically engineered mouse model, using different treatments and timepoints, yielding over a quarter million high quality single cell expression profiles. Consistent with prior studies, we found that RMC-7977 preferentially depleted more poorly differentiated malignant cells from KPC pancreatic tumors by one week of treatment. Residual malignant cells were well differentiated and showed hyperactivation of distinct sets of gastrointestinal and pancreatic progenitor transcription factors. Spatial transcriptomics on the same KPC tumors validated these findings and elucidated clear histological associations with RAS inhibitor treatment. This phenotype was also validated in human tissue explant models using surrogate immunohistochemical markers of cell states. We then decided to investigate the molecular, cellular, and preclinical consequences of combining RAS(ON)-Multi inhibitors with SOC chemotherapy agents. We first employed the well-validated OncoTreat algorithm to predict which PDAC malignant cells may be most susceptible to different SOC agents. Strikingly, we found that nearly all SOC agents were inferred to preferentially target more well-differentiated malignant cells. Indeed, we found that treatment of tumor-bearing KPC mice with gemcitabine + nab-paclitaxel (GnP) led to a depletion of well-differentiated malignant cell states, as measured by single cell regulatory network analysis. This led us to hypothesize that combining RAS inhibition with SOC agents might target complementary sets of malignant cell states, forming a rational basis for combining these agents. Indeed, preclinical intervention studies combining daraxonrasib with GnP showed combinatorial activity in a range of xenograft, syngeneic allograft, and patient-derived xenograft models of PDAC. Ongoing studies in the KPC model system will directly assess the impacts of these combination regimens on malignant PDAC cell states and will directly address the roles of cellular plasticity versus selective cell death in the modulation of cell state in response to RAS inhibition. Together these studies inform the rationale for the combination of RAS(ON) inhibition with cytotoxic chemotherapies in PDAC. Citation Format: Lorenzo Tomassoni, Alvaro Curiel-Garcia, Harika Gundlapalli, Melina Chen, Urszula Wasko-Kornberg, Ximo Pechuan-Jorge, Rashi Raghulan, Yongxian Zhuang, Kevin Contrepois, Steven A. Sastra, Carmine F. Palermo, Ida Aronchik, Jingjing Jiang, Andrea Califano, Mallika Singh, Kenneth P. Olive. RAS inhibition and cytotoxic chemotherapy target complementary cell states in pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: RAS Oncogenesis and Therapeutics; 2026 Mar 5-8; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(5_Suppl_1):Abstract nr A017.

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• Exon inclusion signatures enable accurate estimation of splicing factor activity

  Nature Communications · 2026-03-12

  articleOpen access

  Splicing factors control exon inclusion in messenger RNAs, shaping transcriptome and proteome diversity. Their catalytic activity is regulated by multiple layers, making single-omic measurements on their own fall short in identifying which splicing factors underlie a phenotype. Here, we posit that splicing factor activity, defined as a splicing factor's ability to modulate exon inclusion, can be estimated from changes in exon inclusion signatures. To test this hypothesis, we benchmark methods for constructing splicing factor→exon networks and estimating splicing factor activity. We find that combining RNA-seq perturbation-based networks with VIPER (Virtual Inference of Protein Activity by Enriched Regulon analysis) accurately captures splicing factor activity as modulated by multiple regulatory layers. This approach integrates splicing factor regulation into a single score derived solely from exon inclusion signatures, allowing functional interpretation of heterogeneous conditions. As a proof of concept, we identify recurrent cancer splicing programs, revealing associations with oncogenic- and tumor suppressor-like splicing factors missed by conventional methods. These programs correlate with patient survival and key cancer hallmarks: initiation, proliferation, and immune evasion. Altogether, we show splicing factor activity can be accurately estimated from exon inclusion changes, enabling comprehensive analyses of splicing regulation with minimal data requirements.

  PublisherDOI

• Abstract 6859: Targeting master regulators to reprogram neutrophils and enhance PD-1 blockade efficacy in castration-resistant prostate cancer.

  Cancer Research · 2026-04-03

  articleSenior author

  Abstract Introduction: Neutrophil-mediated immunosuppression limits immunotherapy in Castration-Resistant Prostate Cancer (CRPC), but its mechanisms are unclear. This study aims to identify the drivers of this immunosuppression and evaluate whether targeting Master Regulator (MR) proteins can reprogram neutrophils, remodel the tumor microenvironment (TME), and enhance PD-1 blockade efficacy. Methods: We used orthotopic CRPC models treated with MR inhibitors and anti-PD-1 therapy to assess neutrophil depletion and immune remodeling. Spatial profiling with the 5,000-plex Xenium panel along with cell types annotation via a curated scRNA-seq atlas, revealed a detailed map of tissue organization. Treatment effects on immune populations and spatial reorganization, particularly neutrophils, were quantified. VIPER-based analysis defined MR-driven neutrophil functional states, and spatial mapping was conducted using Xenium data. Finally, ligand-receptor interactions between neutrophils and tumor cells were explored through cell-cell communication network analysis. Summary of unpublished data: We conducted a pilot Xenium study across four treatment arms (vehicle, Trametinib, anti-PD1, and combination) to assess MR inhibition’s effect on immune responses through cell abundance and spatial reorganization. Anti-PD1 induced broad immune recruitment, especially neutrophils, while Trametinib had minimal effect. Combination therapy reduced neutrophil abundance below baseline, attenuating checkpoint blockade-induced neutrophil accumulation. NK/T cells, monocytes, and dendritic cells increased, while macrophages remained stable. Spatial analysis showed that anti-PD1 caused tumor cells to marginalize, while combination therapy partially restored integration. Neutrophils transitioned from marginalization to forming an immunological barrier around tumor cells, and NK/T cells interacted mainly with stromal/myeloid cells, indicating immune exclusion. Despite upregulating PD-L1 in all treatments, combination therapy induced PD-L1 expression without barrier formation, suggesting that spatial organization, not just ligand expression, drives neutrophil-mediated immune exclusion. Conclusion: Treatments reshape tumor-immune architecture without disrupting tissue organization, relying on both immune cell abundance and their spatial distribution within the TME. Anti-PD1 induces broad immune infiltration, but neutrophils form a barrier limiting tumor penetration, which is relieved by the MR-inhibitor Trametinib. Neutrophils upregulate PD-L1 across all treatments, peaking after anti-PD1, while Trametinib and combination therapy drive PD-L1 expression without barrier formation. Citation Format: Melania Franchini, Florencia Picech, Cory Abate-Shen, Andrea Califano. Targeting master regulators to reprogram neutrophils and enhance PD-1 blockade efficacy in castration-resistant prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 6859.

  PublisherDOI

• Abstract 6759: High-throughput drug screening and single-cell network analysis identify rational combination therapies in IDH-mutant glioma

  Cancer Research · 2026-04-03

  articleSenior author

  Abstract IDH-mutant gliomas are lethal brain tumors marked by multiple coexisting malignant cell states, likely to elicit heterogeneous drug sensitivities thus limiting the effectiveness of monotherapy. To address this challenge, we integrated multimodal single-cell analysis and functional high-throughput drug screening to identify and pharmacologically target state-specific vulnerabilities, thus supporting rational combination therapy development. Single-nucleus RNA sequencing (snRNA-seq) of 20 treatment-naïve, low-grade IDH-mutant gliomas, followed by Master Regulator (MR) analysis, identified key proteins representing mechanistic determinants of three established malignant states: astrocyte-like (AC), oligodendrocyte-like (OC), and neural progenitor cell-like (NPC). The analysis revealed that the AC state is transcriptionally orthogonal to OC, whereas the OC and NPC share substantial regulatory architecture. OncoMatch analysis identified patient-derived models (SF10417, SU-A03) that optimally recapitulate the MRs of these malignant subpopulations, supporting screening of a 374 oncology-focused compounds (FDA-approved and investigational) followed by transcriptional profile analysis at 24h, using the PLATE-seq technology, resulting in a comprehensive drug perturbational compendium for IDH-mutant gliomas. OncoTreat analysis prioritized compounds based on their ability to invert the aberrant MR activity signatures of each malignant state, revealing highly cell-state-specific drug sensitivities, supporting the design of rational combination strategies targeting tumor plasticity. For example, we found that AC-like cells may first be primed with the mTOR inhibitor temsirolimus to reprogram them toward a more drug-sensitive OC-like state, thereby converting a resistant lineage into one that is more vulnerable, including to the new class of IDH1 inhibitors. A second-line agent such as the HDAC inhibitor romidepsin or the topoisomerase inhibitor irinotecan can then be used, possibly in combination with IDH1 inhibitors, to target the resulting OC-like and pre-existing OC/NPC cells, thus implementing a two-step, sequential treatment strategy. In parallel, barcode-based lineage tracing in SF10417 and SU-A03 is being used to monitor cell-state stability and plasticity under drug treatment, while top candidate agents and combinations are being validated in patient-derived ex vivo glioma slice cultures that preserve the native microenvironment. Single-cell and spatial transcriptomic profiling (10x Genomics Xenium) of treated slices will map the reprogramming and elimination of malignant subpopulations in situ. Together, this framework provides a blueprint for discovering state-specific dependencies in IDH-mutant glioma and for guiding rational, combination-based strategies to overcome intratumoral heterogeneity. Citation Format: Patrick Kerwin, Luca Zanella, Andrea Califano, . High-throughput drug screening and single-cell network analysis identify rational combination therapies in IDH-mutant glioma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 6759.

  PublisherDOI

• Abstract 1490: A single cell-based protein activity landscape for human small cell lung cancer

  Cancer Research · 2026-04-03

  articleSenior author

  Abstract Small cell lung cancer (SCLC) is a lethal malignancy characterized by rapid metastasis, profound intra-tumor heterogeneity (ITH), and an immunosuppressive tumor immune microenvironment (TIME). The underlying biology of SCLC is poorly understood, and treatment options remain limited. To overcome this, we performed a systematic analysis on a large collection of single-cell RNA-Seq-based SCLC human sample cohort to define the gene regulatory networks and master regulators (MR) driving SCLC ITH and TIME composition. We constructed a single-cell transcriptomic atlas of 182,189 cells from 41 fresh patient-derived SCLC samples (primary and metastatic sites). Tumor and immune cells were cataloged and clustered. To move beyond transcriptional states, we reverse-engineered patient- and cluster-specific regulatory networks using ARACNe and inferred protein activity for >6,500 regulatory and signaling proteins via metaVIPER. This protein activity landscape was used to deconvolute ITH and TIME architecture. The OncoTreat algorithm identified FDA-approved drugs that invert MR activity in matched SCLC cell lines, with subsequent in vivo validation. Our protein activity analysis identified distinct, translationally relevant SCLC tumor and TIME subpopulations governed by specific MR programs. In tumor cells, we defined a proliferative "Tumor Checkpoint" module of MRs as a key determinant of this aggressive disease. Within the TIME, we discovered immune subpopulations with unique biological properties. A genome-wide drug perturbation screen identified potent agents that effectively abrogate the activity of tumor-specific MRs. These candidates demonstrated significant efficacy in inducing tumor cell death in preclinical in vivo models. We present the largest single-cell protein activity atlas of SCLC, providing a high-resolution view of the regulatory networks underlying its ITH and TIME. We computationally derived and preclinically validated novel therapeutic strategies that target master regulators of distinct tumor and immune subpopulations, offering a promising path to overcome therapeutic resistance in SCLC. Citation Format: Lucas ZhongMing Hu, Anish Thomas, Andrea Califano. A single cell-based protein activity landscape for human small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1490.

  PublisherDOI

• Abstract 6858: Single-cell elucidation of molecularly distinct states and therapeutic vulnerabilities in IDH-mutant glioma.

  Cancer Research · 2026-04-03

  articleSenior author

  Abstract IDH-mutant gliomas, including oligodendrogliomas (IDH-O) and astrocytomas (IDH-A), are a molecularly defined class of fatal primary brain tumors characterized by mutations in the IDH1 and IDH2 genes. Despite advances in standard-of-care approaches, prognosis remains poor with median survival rates of 5-15 years. Substantial inter- and intra-tumor heterogeneity limits the efficacy of current monotherapies and necessitates ad hoc combination strategies targeting distinct tumor subpopulations. To comprehensively characterize the cellular landscape of IDH-mutant gliomas, we generated >250k high-quality single-nucleus transcriptomic profiles from 20 IDH-mutant glioma tumors (grade II and grade III; 10 IDH-O; 10 IDH-A) obtained from the Molecular Pathology Shared Resource (MPSR) Tumor Bank at Columbia University. Gene expression analysis revealed glioma cells, microglia, neurons and mature oligodendrocytes as the predominant cell types in both IDH-O and IDH-A, with a striking depletion of microglia in IDH-O. Network-based VIPER analysis of single-nucleus profiles identified Master Regulator (MR) proteins representing molecular dependencies of three previously described glioma states: astrocyte-like (AC), oligodendrocyte-like (OC) and neural-progenitor-like (NPC). Notably, the AC state was transcriptionally orthogonal to OC, whereas OC and NPC largely shared their regulatory architecture. To predict rational combination therapy candidates, we employed NYS CLIA-certified OncoTarget and OncoTreat algorithms. OncoTarget identifies small molecule inhibitors targeting individual state-specific MRs, while OncoTreat predicts candidate drugs by assessing their ability to invert the activity of glioma-specific MRs, leveraging large-scale drug perturbation assays generated by PLATE-seq. Specifically, we generated a library of genome-wide RNA-seq profiles from patient-matched in vitro models, one adherent cell line (SF10417) and one neurosphere (SUA03), 24 hours after treatment with 374 compounds from a library of FDA approved and investigational compounds. OncoTarget uncovered distinct pathway dependencies across glioma states, including STAT3/PI3K/AKT in AC cells, PDGFRA in OC, and RTK/EGFR/MET signaling in NPC cells. OncoTreat identified CNS-permeable agents predicted to invert glioma-specific MR programs. Future work will include validation of candidate compounds in patient-derived acute slice cultures to assess single-cell responses within an intact microenvironment. Complementary Xenium spatial profiling will map the microenvironmental context and cell-cell communication of molecularly distinct subpopulations, informing rational therapeutic strategies. Overall, our study establishes a generalizable framework for precision oncology in transcriptionally complex tumors and provides actionable targets for clinical translation. Citation Format: Luca Zanella, Patrick M. Kerwin, Mikko Turunen, Peter A. Sims, Peter D. Canoll, Andrea Califano. Single-cell elucidation of molecularly distinct states and therapeutic vulnerabilities in IDH-mutant glioma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 6858.

  PublisherDOI

• Table S1 from OncoLoop: A Network-Based Precision Cancer Medicine Framework

  2025-12-11

  articleOpen access

  <p>Supplementary Table 1: Phenotypic analysis of the GEMMs</p>

  PublisherDOI

• Table S4 from A Transcriptome-Based Precision Oncology Platform for Patient–Therapy Alignment in a Diverse Set of Treatment-Resistant Malignancies

  2025-12-11

  articleOpen accessSenior author

  <p>Curated list of proteins with high-affinity inhibitor drugs for OncoTarget analysis.</p>

  PublisherDOI

Recent grants

• Structural and Functional Biology-based analysis of non-oncogene cancer dependencies

  NIH · $17.0M · 2021–2022

• Gene Network Perturbations in Alcohol Dependence - A Systems BiologyApproach

  NIH · $5.6M · 2013–2024

• NIH Grant R01GM085659

  NIH · $2.0M · 2012

• NIH Grant U01HL111566

  NIH · $799k · 2014

• NIH Grant R01AI066116

  NIH · $2.5M · 2011

Frequent coauthors

• Mariano J. Alvarez

  252 shared

• Mukesh Bansal

  162 shared

• Charles Karan

  158 shared

• Michael M. Shen

  140 shared

• Cory Abate‐Shen

  Columbia University

  136 shared

• Ronald Realubit

  131 shared

• Kenneth P. Olive

  124 shared

• Jeffrey N. Bruce

  Columbia University

  113 shared

Awards & honors

• Outstanding Investigator Award from the National Cancer Inst…
• Ruth Leff Siegel Award for pancreatic cancer research (2019)
• Fellow of the American Association for the Advancement of Sc…
• Fellow of the International Society for Computational Biolog…
• Fellow of the Institute of Electrical and Electronics Engine…