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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240116T100000
DTEND;TZID=America/New_York:20240116T110000
DTSTAMP:20260423T183712
CREATED:20231228T161103Z
LAST-MODIFIED:20240116T220945Z
UID:7581-1705399200-1705402800@componcmsk.org
SUMMARY:Computational Oncology Seminar Series\, Dr. Sanja Vickovic
DESCRIPTION:To view the seminar recording\, please click here \nTalk Title: \nDeciphering tissue pathogenesis with spatial sequencing \nAbstract: \nSpatial and molecular characteristics determine tissue function\, yet high-resolution methods to capture both concurrently are lacking. In recent years\, we developed high-definition spatial transcriptomics and multi-omics technologies\, which captures RNA\, protein information or microbiota from histological tissue sections on spatially barcoded arrays. Today\, I will present how these different technologies were developed and are applied in complex biological systems. 
URL:https://componcmsk.org/event/computational-oncology-seminar-series-dr-sanja-vickovic/
LOCATION:Computational Oncology Research Campus (Joy Building) 321 E 61st St.
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=application/pdf:https://componcmsk.org/wp-content/uploads/2023/12/Sanja_Vickovic_Flyer_2.pdf
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20231212T100000
DTEND;TZID=America/New_York:20231212T110000
DTSTAMP:20260423T183712
CREATED:20231208T233138Z
LAST-MODIFIED:20231212T182055Z
UID:7566-1702375200-1702378800@componcmsk.org
SUMMARY:Computational Oncology Seminar Series\, Dr. Itai Yanai
DESCRIPTION:To view the seminar recording\, please click here \nTalk Title: \nCellular plasticity and developmental constraints in tumorigenesis and drug resistance \nAbstract: \nCellular plasticity is emerging as an important driving force underlying cancer progression and drug resistance. In this talk\, I will discuss the concept of cancer cell states present in the tumor prior to treatment\, as well as those that accompany resistance to increasing drug doses. In particular\, I will discuss work published in our recent manuscript ‘Cancer cell states recur across tumor types and form specific interactions with the tumor microenvironment’ and recent developments in this project. Second\, I will discuss our new work of ‘Drug-induced adaptation along a resistance continuum in cancer cells’. In this work we demonstrate that resistance develops through trajectories of cell state transitions accompanied by a progressive increase in cell fitness\, which we denote the ‘resistance continuum’. This cellular adaptation involves a step-wise assembly of gene expression programs and epigenetic reinforcement of cell states. These processes are underpinned by phenotypic plasticity/dedifferentiation\, physiological adaptation to stress and metabolic reprogramming. Our results support the notion that stemness programs\, commonly viewed as a proxy for phenotypic plasticity\, enable adaptation\, rather than providing a proximal resistance mechanism. Through systematic genetic perturbations\, we identify an acquisition of progressive metabolic dependencies\, exposing a spectrum of vulnerabilities that can be potentially exploited therapeutically. The concept of the resistance continuum highlights the dynamic nature of cellular adaptation and calls for complementary therapies directed at the mechanisms underlying adaptive cell state transitions. 
URL:https://componcmsk.org/event/computational-oncology-seminar-series-dr-itai-yanai/
LOCATION:Computational Oncology Research Campus (Joy Building) 321 E 61st St.
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=application/pdf:https://componcmsk.org/wp-content/uploads/2023/12/Flyer_Dr_Itai_Yanai_4.pdf
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20231121T100000
DTEND;TZID=America/New_York:20231121T110000
DTSTAMP:20260423T183712
CREATED:20231026T155229Z
LAST-MODIFIED:20231121T210549Z
UID:7463-1700560800-1700564400@componcmsk.org
SUMMARY:Computational Oncology Seminar Series\, Dr. Jean Fan
DESCRIPTION:For seminar recording\, please click here \nTalk Title: \nComparative spatial omics analysis across length scales \nAbstract: \nSpatially resolved omics technologies provide molecular profiling of cells while preserving their organization within tissues. Such technologies provide the opportunity to evaluate spatial molecular comparisons across healthy versus diseased tissues. In this talk\, I will highlight two tools my lab has recently developed for such comparative spatial omics analysis. First\, for structurally similar tissues\, we developed STalign to enable structural alignment within and across spatial transcriptomic technologies using diffeomorphic metric mapping. As such\, STalign enables comparing molecular and cell-type compositions at aligned structurally-matched spatial locations across samples. I will demonstrate how we applied STalign to align ST datasets within and across technologies as well as to align ST datasets to a 3D common coordinate framework. I will highlight how STalign achieves high gene expression and cell-type correspondence across matched spatial locations that is significantly improved over manual and landmark-based affine alignments. Second\, we developed CRAWDAD to quantify cell-type spatial relationships across length scales to advance our understanding of the association between cell-type organization and tissue function. I will highlight the utility of such multi-scale characterization on simulated data\, recapitulate expected cell-type spatial relationships in tissues such as the mouse brain and embryo\, and delineate functionally relevant spatial-defined cell-type subsets in the human spleen. 
URL:https://componcmsk.org/event/computational-oncology-seminar-series-dr-jean-fan/
LOCATION:Joy Building\, 321 E 61st St.
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=application/pdf:https://componcmsk.org/wp-content/uploads/2023/10/Flyer_Dr_Jean_Fan-1.pdf
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20231031T100000
DTEND;TZID=America/New_York:20231031T110000
DTSTAMP:20260423T183712
CREATED:20230925T154253Z
LAST-MODIFIED:20231031T202609Z
UID:7282-1698746400-1698750000@componcmsk.org
SUMMARY:Computational Oncology Seminar Series\, Dr. Jakob Nikolas Kather
DESCRIPTION:For seminar recording\, please click here \nTalk Title: \nArtificial Intelligence in Precision Oncology \nAbstract: \nPrecision oncology requires complex biomarkers which are often based on molecular and genetic tests of tumor tissue. For many of these tests\, universal implementation in clinical practice is limited. However\, for virtually every cancer patient\, pathology tissue slides stained with hematoxylin and eosin (H&E) are available. Artificial intelligence (AI) can extract biomarkers for better treatment decisions from these images. This talk will summarize the state of the art of AI in oncology for precision oncology biomarkers. It will cover the technical foundations\, emerging use cases and established applications which are already available for clinical use. 
URL:https://componcmsk.org/event/computational-oncology-seminar-series-dr-jakob-nikolas-kather/
LOCATION:Rockefeller Research Laboratories- 116
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=application/pdf:https://componcmsk.org/wp-content/uploads/2023/09/Flyer_Dr_Jakob_Nikolas_Kather.pdf
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230919T100000
DTEND;TZID=America/New_York:20230919T110000
DTSTAMP:20260423T183712
CREATED:20230821T184324Z
LAST-MODIFIED:20231031T202628Z
UID:7247-1695117600-1695121200@componcmsk.org
SUMMARY:Computational Oncology Seminar Series\, Dr. Rachel J. O'Neill
DESCRIPTION:For seminar recording\, please click here \nTalk Title: \nUsing T2T-level comparative genomics to study repeat biology \nAbstract: \nMobile elements and highly repetitive regions are potent sources of lineage-specific genomic innovation and are integral to the structure and function of eukaryotic cells. Recent efforts employing long-read based genome assembly\, functional and repeat analyses across multiple marsupial and primate lineages have afforded the opportunity to distinguish the key elements participant in centromere evolution and chromosome rearrangement from those that establish centromere stability. Moreover\, as part of the Telomere-to-Telomere (T2T) consortium\, we have completed a comprehensive repeat annotation for the first complete human reference genome. Utilizing PRO-seq to detect nascent transcription and nanopore sequencing to delineate CpG methylation profiles\, we defined the structure of transcriptionally active retroelements in humans. Using a comparative cytogenomics approach\, these studies provide insight into the diversity\, distribution and evolution of repetitive regions that shape chromosome structure and evolution in species groups experiencing rapid karyotypic change. 
URL:https://componcmsk.org/event/computational-oncology-seminar-series-dr-rachel-oneill/
LOCATION:Joy Building\, 321 E 61st St.
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=application/pdf:https://componcmsk.org/wp-content/uploads/2023/08/Flyer_Dr_Rachel_Oneill.pdf
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230620T100000
DTEND;TZID=America/New_York:20230620T110000
DTSTAMP:20260423T183712
CREATED:20230620T175610Z
LAST-MODIFIED:20231031T204542Z
UID:7196-1687255200-1687258800@componcmsk.org
SUMMARY:Computational Oncology Seminar Series\, Dr. Marcin Imieliński
DESCRIPTION:For seminar recording\, please click here \nTalk Title: \nLeveraging mass balance and long DNA molecules to study structural variant mutational processes in cancer \nAbstract: \nGenome structure\, like other physical phenomena\, obeys the simple principle of mass balance. I will show how we can apply this principle algorithmically to assess what structural variants (SVs) are missing from short-read whole genomes. These include neotelomeres and footprints of viral-driven chromosomal instability. We can further use mass balance to rigorously demonstrate the extent with which aberrant homologous recombination (HR) shapes cancer genome structure\, which we validate with long-read and linked-read whole genome sequencing. We next extend this principle to tumors defective in DNA repair to uncover new SV scars of HR deficiency. Leveraging the ability of long molecules to resolve somatic SV phase\, we solve a long-standing paradox in the HR deficiency field linking the chromosomal-scale aberrations observed in repair deficient cells to BRCA1- and BRCA2-deficiency specific base-level alterations. These findings have implications for backup repair pathways in HR deficient tumors and provide additional ingredients for whole genome sequencing biomarkers with near-term clinical applicability. 
URL:https://componcmsk.org/event/computational-oncology-seminar-series-dr-marcin-imielinski/
LOCATION:Joy Building\, 321 E 61st St.
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=application/pdf:https://componcmsk.org/wp-content/uploads/2023/06/Flyer_Dr_Marcin_Imielinski.pdf
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20230517
DTEND;VALUE=DATE:20230519
DTSTAMP:20260423T183712
CREATED:20230517T141739Z
LAST-MODIFIED:20230517T152005Z
UID:7186-1684281600-1684454399@componcmsk.org
SUMMARY:2023 Emerging Leaders in Computational Oncology
DESCRIPTION:
URL:https://componcmsk.org/event/computational-oncology-emerging-leaders-2023/
LOCATION:Day 1: MSK Rockefeller Research Laboratories <br>Day 2: MSK Joy Building <br>\, Memorial Sloan Kettering Cancer Center\, New York\, NY\, 10065\, United States
CATEGORIES:ELS
ATTACH;FMTTYPE=image/png:https://componcmsk.org/wp-content/uploads/2023/05/Screenshot-2023-05-17-at-10.23.33-AM.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230516T100000
DTEND;TZID=America/New_York:20230516T110000
DTSTAMP:20260423T183712
CREATED:20230516T191906Z
LAST-MODIFIED:20231031T204614Z
UID:7178-1684231200-1684234800@componcmsk.org
SUMMARY:Computational Oncology Seminar Series\, Dr. Raul Rabadan
DESCRIPTION:For seminar recording\, please click here \nTalk Title: \nSome mysteries about viruses and cancer \nAbstract: \nIt has been estimated that 15%-20% of human cancers are attributable to infections\, mostly by carcinogenic viruses. The incidence varies worldwide\, with a majority affecting developing countries. Here\, we present a comparative analysis of virus-positive and virus-negative tumors in nine cancers linked to five viruses. We find that virus-positive tumors occur more frequently in males and show geographical disparities in incidence. Genomic analysis of 1\,658 tumors reveals virus-positive tumors exhibit distinct mutation signatures and driver gene mutations and possess a lower somatic mutation burden compared to virus-negative tumors of the same cancer type. For example\, compared to the respective virus-negative counterparts\, virus-positive cases across different cancer histologies had less often mutations of TP53 and deletions of 9p21.3/CDKN2A-CDKN1A; Epstein-Barr virus-positive (EBV+) gastric cancer had more frequent mutations in EIF4A1 and ARID1A and less marked mismatch repair deficiency signatures; and EBV-positive cHL had fewer somatic genetic lesions of JAK-STAT\, NF-κB\, PI3K-AKT and HLA-I genes and a less pronounced activity of the aberrant somatic hypermutation signature. In cHL\, we also identify germline homozygosity in HLA class I as a potential risk factor for the development of EBV-positive Hodgkin lymphoma. Finally\, an analysis of clinical trials of PD-(L)1 inhibitors in four virus-associated cancers suggested an association of viral infection with higher response rate in patients receiving such treatments\, which was particularly evident in gastric cancer and head and neck squamous cell carcinoma. These results illustrate the epidemiological\, genetic\, prognostic\, and therapeutic trends across virus-associated malignancies.
URL:https://componcmsk.org/event/computational-oncology-seminar-series-dr-raul-rabadan/
LOCATION:Joy Building\, 321 E 61st St.
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=application/pdf:https://componcmsk.org/wp-content/uploads/2023/05/Flyer_Dr_Raul_Rabadan.pdf
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230502T100000
DTEND;TZID=America/New_York:20230502T110000
DTSTAMP:20260423T183712
CREATED:20230403T173135Z
LAST-MODIFIED:20231031T204703Z
UID:7155-1683021600-1683025200@componcmsk.org
SUMMARY:Machine Learning Seminar Series\, Dr. Dmitry Krotov
DESCRIPTION:For seminar recording\, please click here \nTalk Title: \nModern Hopfield Networks for Novel Transformer Architectures  \nAbstract: \nModern Hopfield Networks or Dense Associative Memories are recurrent neural networks with fixed point attractor states that are described by an energy function. In contrast to conventional Hopfield Networks\, which were popular in the 1980s\, their modern versions have a very large memory storage capacity\, which makes them appealing tools for many problems in machine learning and cognitive and neuro-sciences. In this talk I will introduce an intuition and a mathematical formulation of this class of models\, and will give examples of problems in AI that can be tackled using these new ideas. Particularly\, I will introduce an architecture called Energy Transformer\, which replaces the conventional attention mechanism with a recurrent Dense Associative Memory model. I will explain the theoretical principles behind this architectural choice and show promising empirical results on challenging computer vision and graph network tasks. 
URL:https://componcmsk.org/event/machine-learning-seminar-series-dr-dmitry-krotov/
LOCATION:Joy Building\, 321 E 61st St.
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=application/pdf:https://componcmsk.org/wp-content/uploads/2023/04/Flyer_Dr_Dmitry_Krotov.pdf
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230427T100000
DTEND;TZID=America/New_York:20230427T110000
DTSTAMP:20260423T183712
CREATED:20230403T172705Z
LAST-MODIFIED:20231031T205253Z
UID:7152-1682589600-1682593200@componcmsk.org
SUMMARY:Computational Oncology Seminar Series\, Dr. Elham Azizi
DESCRIPTION:For seminar recording\, please click here \nTalk Title: \nProbabilistic Modeling of Dynamics of the Tumor Microenvironment \nAbstract: \nCancer therapies succeed only in a subset of patients partly due to the heterogeneity of cells across and within tumors. Single-cell and spatial genomic technologies present exciting opportunities to characterize unknown cell types in complex tissues such as tumor microenvironments and elucidate their interactions\, circuitry\, and role in driving response to therapies. However\, analyzing and integrating single-cell data across conditions\, patients\, time points\, and data modalities involve significant statistical and computational challenges. I will present a set of probabilistic and deep generative models developed for addressing these problems and modeling temporal and spatial dynamics of key immune subsets defining cancer progression and response to immunotherapy. I will also present Starfysh for spatial mapping of heterogeneous cell states and crosstalk in complex tissues\, from the integration of spatial transcriptomics and histology images.
URL:https://componcmsk.org/event/computational-oncology-seminar-series-dr-elham-azizi/
LOCATION:Joy Building\, 321 E 61st St.
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=application/pdf:https://componcmsk.org/wp-content/uploads/2023/04/Flyer_Dr_Elham_Azizi.pdf
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230321T100000
DTEND;TZID=America/New_York:20230321T110000
DTSTAMP:20260423T183712
CREATED:20230309T154705Z
LAST-MODIFIED:20230321T155543Z
UID:7146-1679392800-1679396400@componcmsk.org
SUMMARY:Computational Oncology Seminar Series\, Dr. Gavin Ha
DESCRIPTION:For Meeting Recording\, please click here. Passcode: 27097062 \nTalk Title: \nMethods for tumor phenotype classification from circulating tumor DNA \nAbstract: \nAn accurate diagnosis of the tumor histology is essential for clinical care. Aggressive tumor phenotypes can emerge through subtype changes and lineage plasticity as major mechanisms of treatment resistance in cancer. Therefore\, distinguishing tumor phenotypes has clinical relevance in view of therapeutic response\, but the need for a biopsy to diagnose tumor histology can be challenging. Circulating tumor DNA (ctDNA) released from tumor cells into the blood is a non-invasive “liquid biopsy” solution for addressing challenges in tissue accessibility. Current research and clinical efforts have focused on the detection of genetic mutations from ctDNA sequencing as potential biomarkers. However\, genomic alterations do not always define tumor phenotypes nor fully explain treatment resistance. Recent advances now demonstrate that epigenetic information can be ascertained from profiling nucleosome positioning and accessibility in ctDNA. In this talk\, I will describe how we applied this concept to develop computational methods for predicting transcriptional activity and classifying tumor phenotypes in breast\, prostate\, and lung cancers. We established a unique resource of mouse plasma from patient-derived xenografts to dissect the transcriptional activity of tumor phenotypes directly from ctDNA and to inform a suite of prediction models that can quantify phenotype heterogeneity in patients. These tools provide a framework that extends the utility of ctDNA beyond genomic assessments with important implications for molecular classification and precision oncology. 
URL:https://componcmsk.org/event/computational-oncology-seminar-series-dr-gavin-ha/
LOCATION:Joy Building\, 321 E 61st St.
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=application/pdf:https://componcmsk.org/wp-content/uploads/2023/03/Flyer_Dr_Gavin_Ha.pdf
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230221T100000
DTEND;TZID=America/New_York:20230221T110000
DTSTAMP:20260423T183712
CREATED:20230215T001650Z
LAST-MODIFIED:20231031T210708Z
UID:7067-1676973600-1676977200@componcmsk.org
SUMMARY:Computational Oncology Seminar Series\, Dr. Joakim Lundeberg
DESCRIPTION:For seminar recording\, please click here \nTalk Title: \nCapturing and exploring the transcriptional and genomic landscape in tissues in health and disease \nAbstract: \nTissue represents an ecosystem of different cells carrying out different tasks. Specific types of cells exist in every organ\, and serve specialized functions defined by the specific genes and proteins active in each cell type. Comprehensive maps of molecularly defined human cell types are underway through the Human Cell Atlas effort using primarily single-cell RNA sequencing. The technologies to assemble spatial maps that will describe and define the cellular basis of health and disease is less well clear although remarkable improvements have been published in recent years. We have developed and established the Spatial Transcriptomics technology\, in which tissue imaging is merged with spatial RNA sequencing and resolved by computational means. Spatial Transcriptomics technology was the first method to provide unbiased whole transcriptome analysis with spatial information from tissue using barcoded array surfaces and has since its initial publication been used in multiple biological systems in health and disease. This presentation will cover novel methodological and analytical aspects of the technology in the context of biological applications from cell atlas\, neurology and cancer.
URL:https://componcmsk.org/event/computational-oncology-seminar-series-dr-joakim-lundeberg/
LOCATION:Zuckerman Research Center Auditorium\, 417 E 68th Street\, New York\, NY\, 10065\, United States
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=application/pdf:https://componcmsk.org/wp-content/uploads/2023/02/Flyer_Dr_Joakim_Lundeberg.pdf
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230117T100000
DTEND;TZID=America/New_York:20230117T110000
DTSTAMP:20260423T183712
CREATED:20221215T175048Z
LAST-MODIFIED:20231031T211250Z
UID:7028-1673949600-1673953200@componcmsk.org
SUMMARY:Computational Oncology Seminar Series\, Dr. Melissa Boneta Davis
DESCRIPTION:For seminar recording\, please click here \nTalk Title: \nGenomic landscapes of Breast Cancer (Racial/Ancestry) Disparities \nAbstract: \nOverview of the emerging findings from genome-wide studies of African-enriched cohorts of breast cancer patients. We will discuss results of multiple ‘omic’ approaches\, including genotype associations\, whole genome sequence characterizations and transcriptomic studies. 
URL:https://componcmsk.org/event/computational-oncology-seminar-series-dr-melissa-boneta-davis/
LOCATION:Joy Building\, 321 E 61st St.
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=application/pdf:https://componcmsk.org/wp-content/uploads/2022/12/Flyer_Dr_Melissa_B_Davis.pdf
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221213T100000
DTEND;TZID=America/New_York:20221213T110000
DTSTAMP:20260423T183712
CREATED:20221115T201355Z
LAST-MODIFIED:20231031T211547Z
UID:6931-1670925600-1670929200@componcmsk.org
SUMMARY:Computational Oncology Seminar Series\, Dr. Ashley Laughney
DESCRIPTION:For seminar recording\, please click here \nTalk Title: \nSystems analysis of ligand effects induced by chromosomal instability on the tumor ecosystem \nAbstract: \n Multicellular programs underly emergent phenotypes in health and disease. Yet\, deciphering higher-order functional interactions amongst cell types remains a major challenge. Cell-to-cell communication often takes the form of ligands emanating from “donor” cells to receptors expressed on “target” cells. Complimentary ligand-receptor pairs are well annotated\, and their co-occurrence can be used to identify putative interactions from single cell data. However\, no methods exist to quantify cellular responses to ligand-receptor-mediated interactions in the microenvironment. Thus\, we developed ContactTracing – a fundamentally new\, systems level approach that exploits inter- and intra-sample variability to infer ligand effects on gene expression in target (receptor-expressing) cells without prior knowledge of downstream signaling. Foundational work towards benchmarking and validation of this method was performed in isogenic breast cancer models distinguished by tumor cell-intrinsic rates of chromosome missegregation (a cellular process called chromosomal instability\, or CIN). Through this\, we identified tumor ligands emanating from an endoplasmic reticulum (ER)-stress response as potential mediators of immune suppression in chromosomally unstable tumors. Indeed\, CIN-induced chronic STING activation led to rapid interferon-selective desensitization and a switch to ER-stress-dependent transcription. Moreover\, inhibition of chronic STING – or key mediators of its unfolded protein response to ER-stress – suppressed metastasis in syngeneic models of melanoma\, breast and colorectal cancer; validating this innovative methodology and identifying a critical mediator of cancer progression.
URL:https://componcmsk.org/event/computational-oncology-seminar-series-dr-ashley-laughney/
LOCATION:Joy Building\, 321 E 61st St.
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=application/pdf:https://componcmsk.org/wp-content/uploads/2022/11/Flyer_Dr_Ashley_Laughney.pdf
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221206T100000
DTEND;TZID=America/New_York:20221206T110000
DTSTAMP:20260423T183712
CREATED:20221103T140113Z
LAST-MODIFIED:20231031T202540Z
UID:6572-1670320800-1670324400@componcmsk.org
SUMMARY:Machine Learning Seminar Series\, Dr. Scott Linderman
DESCRIPTION:For seminar recording click here \nTalk Title: \nLatent States of Brains and Behavior \nAbstract: \nNew recording technologies are transforming neuroscience\, allowing us to measure the spiking activity of thousands of neurons in freely behaving animals. These technologies offer exciting opportunities to link brain activity to behavioral output\, but they also pose serious statistical challenges. Neural and behavioral data are noisy\, high-dimensional time-series with complex dynamics. I will present our work on state space models (SSMs) for neural and behavioral time-series. The key idea is that underlying these high-dimensional data are low-dimensional latent states\, which shed light on how neural circuits compute and how natural behavior is organized. First\, I will present new models that decompose natural behavior into sequences of discrete\, stereotyped\, and reusable actions called “syllables\,” while simultaneously allowing for continuous variations in speed or vigor. By disentangling discrete and continuous variability\, we obtain parsimonious representations of moment-to-moment behavior that correlate with fluctuations of dopamine in the striatum. Next\, I will show how the same simple building blocks can be composed into flexible and expressive models for neural recordings. Our models are not only among the most accurate models for multi-neuronal spike trains\, they also achieve state-of-the-art performance on a host of other sequence prediction benchmarks in machine learning. Together\, these lines of work highlight how advances in machine learning and statistics offer powerful new tools for linking brain activity and behavior.
URL:https://componcmsk.org/event/machine-learning-seminar-series-dr-scott-linderman/
LOCATION:Joy Building\, 321 E 61st St.
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=application/pdf:https://componcmsk.org/wp-content/uploads/2022/11/Flyer_Dr_Scott_Linderman-1.pdf
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221115T100000
DTEND;TZID=America/New_York:20221115T110000
DTSTAMP:20260423T183712
CREATED:20221020T193829Z
LAST-MODIFIED:20231031T201804Z
UID:6538-1668506400-1668510000@componcmsk.org
SUMMARY:Computational Oncology Seminar Series\, Dr. Itay Tirosh
DESCRIPTION:For seminar recording\, please click here \nTalk Title: \nDissecting intra-tumor heterogeneity by single cell RNA-seq  \n  \nAbstract: \nEach tumor is composed of diverse malignant\, immune and stromal cells that interact with one another and collectively determine tumor biology and clinical phenotypes. Over the past nine years\, we have been applying single cell RNA-seq (scRNA-seq) to diverse clinical tumor samples to comprehensively characterize the cellular diversity within tumors and explore the function of distinct tumor subpopulations. In this talk\, I will describe our work on specific cancer types (e.g. glioma) and our pan-cancer integrative analysis of intra-tumor heterogeneity (ITH). We identify consistent patterns of heterogeneity across tumors\, including expression meta-programs\, consisting of dozens of genes that are coordinately upregulated in subpopulations of cells within many tumors. The meta-programs cover diverse cellular processes including both generic (e.g. cell cycle and stress) and lineage-specific patterns that influence metastasis\, response to treatments and other tumor phenotypes. The systematic characterization of ITH will help to understand tumor biology and to design improved therapeutic strategies such as combination treatments and differentiation therapies. 
URL:https://componcmsk.org/event/computational-oncology-seminar-series-dr-itay-tirosh/
LOCATION:Zuckerman Research Center Auditorium\, 417 E 68th Street\, New York\, NY\, 10065\, United States
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=application/pdf:https://componcmsk.org/wp-content/uploads/2022/10/Flyer_Dr_Itay_Tirosh.pdf
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221101T100000
DTEND;TZID=America/New_York:20221101T110000
DTSTAMP:20260423T183712
CREATED:20221020T194911Z
LAST-MODIFIED:20221103T142455Z
UID:6543-1667296800-1667300400@componcmsk.org
SUMMARY:Machine Learning Seminar Series\, Dr. Jennifer Dy
DESCRIPTION:Meeting Recording: \nhttps://web.microsoftstream.com/video/c84847fc-b1d2-4ec2-a7c3-5243f063cc3f \nTalk Title: \nLearning Interpretable Models on Complex Medical Data \nAbstract: \nMachine learning as a field has become more and more important due to the ubiquity of data collection in various disciplines. Coupled with this data collection is the hope that new discoveries or knowledge can be learned. My research spans both fundamental research in machine learning and their application to biomedical imaging\, health\, science and engineering. Multi-disciplinary research is instrumental to the growth of the various areas involved. In many applications\, data is often complex\, high-dimensional and multi-faceted\, where multiple possible interpretations are inherent in the data. Fortunately\, domain scientists often have rich knowledge that can guide data driven methods. Thus\, it is important to enable incorporation of domain input into the design of algorithms. Furthermore\, for clinicians and domain scientists to trust and use the results of learning algorithms\, not only are models necessary to be accurate but it is also imperative for learning models to be interpretable. In this talk\, I highlight these challenges through our experience in collaborative research working on discovering disease subtypes and then provide examples of how these challenges led to innovations in machine learning and to new discoveries. I will then provide an overview of our other novel machine learning algorithm development projects that are inspired by complex medical data.
URL:https://componcmsk.org/event/machine-learning-seminar-series-dr-jennifer-dy/
LOCATION:Zuckerman Research Center Auditorium\, 417 E 68th Street\, New York\, NY\, 10065\, United States
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=application/pdf:https://componcmsk.org/wp-content/uploads/2022/10/Flyer_Dr_Jennifer_Dy.pdf
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20221018T100000
DTEND;TZID=America/New_York:20221018T110000
DTSTAMP:20260423T183712
CREATED:20221020T200609Z
LAST-MODIFIED:20231101T174006Z
UID:6546-1666087200-1666090800@componcmsk.org
SUMMARY:Computational Oncology Seminar Series\, Dr. Rameen Beroukhim
DESCRIPTION:For seminar recording\, please click here \nTalk Title:  \nDetecting effects of alterations in chromosome structure on cancer cellular fitness \nAbstract: \nStructural variants—alterations in chromosome structure—affect far more of the cancer genome than any other type of genetic event. Indeed\, large-scale aneuploidies were the first genetic alteration posited to contribute to cancer. Because of their complexity and long-range genomic effects\, however\, their impacts on cancer evolution have been poorly defined. Even the genes that account for those impacts are not known for many of the most common structural variants. We describe new methods to interrogate structural variants including large-scale aneuploidies and their implications for cancer development and progression.
URL:https://componcmsk.org/event/computational-oncology-seminar-series-dr-rameen-beroukhim/
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=application/pdf:https://componcmsk.org/wp-content/uploads/2022/10/Flyer_Dr_Rameen_Beroukhim.pdf
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20210311T100000
DTEND;TZID=America/New_York:20210311T110000
DTSTAMP:20260423T183712
CREATED:20201029T142957Z
LAST-MODIFIED:20210309T213424Z
UID:5837-1615456800-1615460400@componcmsk.org
SUMMARY:Computational Oncology Seminar Series\, Dr. Andrea Sottoriva
DESCRIPTION:Talk Title:  \nMeasuring and predicting cancer evolution with genomic data \n  \nAbstract: \nWe combine theoretical population genetics models of evolving populations with machine learning methods to analyze cancer genomic data\, with specific focus on whole-genome sequencing. This allows deconvoluting the signal in the data to measure clonal structures\, selective advantage coefficients of subclones\, and mutation rates\, from human tumor samples. The use of a model-based approach also allows to parameterise predictive models to be ‘played forward’ with the aim of anticipating disease evolution.
URL:https://componcmsk.org/event/computational-oncology-seminar-series-dr-andrea-sottoriva/
LOCATION:Virtual
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=application/pdf:https://componcmsk.org/wp-content/uploads/2020/10/Andrea-Sottoriva-3.11.21.pdf
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20210216T100000
DTEND;TZID=America/New_York:20210216T110000
DTSTAMP:20260423T183712
CREATED:20201029T142815Z
LAST-MODIFIED:20210127T215234Z
UID:5835-1613469600-1613473200@componcmsk.org
SUMMARY:Computational Oncology Seminar Series\, Dr. Inigo Martincorena
DESCRIPTION:Talk Title: \nSomatic mutation and clonal expansion in normal tissues \n  \nAbstract: \nCancers develop by somatic mutation and clonal selection within our tissues. Over the past decade\, the ability to sequence cancer genomes has transformed our understanding of the genetics and evolution of a wide range of cancers. However\, owing to technical limitations\, little is known about the earliest steps of cancer and how cells in our tissues accumulate mutations during normal ageing and in their progression towards cancer. In this talk\, I will present our work unveiling a hidden and unexpected world of cellular competition and somatic evolution in human healthy tissues\, with implications for our understanding of cancer and ageing. \n  \n 
URL:https://componcmsk.org/event/computational-oncology-seminar-series-dr-inigo-martincorena/
LOCATION:Virtual
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=application/pdf:https://componcmsk.org/wp-content/uploads/2020/10/Inigo-Martincorena-Flyer-2.16.21.pdf
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20210112T100000
DTEND;TZID=America/New_York:20210112T110000
DTSTAMP:20260423T183712
CREATED:20201029T142618Z
LAST-MODIFIED:20210108T220039Z
UID:5829-1610445600-1610449200@componcmsk.org
SUMMARY:Computational Oncology Seminar Series\, Dr. Faiyaz Notta
DESCRIPTION:Talk Title:  \nMolecular subtypes of Pancreatic Cancer and Ph+ lymphoblastic leukemia  \n 
URL:https://componcmsk.org/event/january-seminar-2021/
LOCATION:Virtual
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=application/pdf:https://componcmsk.org/wp-content/uploads/2020/10/F.Notta-Flyer-1.12.21.pdf
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201208T100000
DTEND;TZID=America/New_York:20201208T110000
DTSTAMP:20260423T183712
CREATED:20200820T191145Z
LAST-MODIFIED:20201207T175555Z
UID:5415-1607421600-1607425200@componcmsk.org
SUMMARY:Computational Oncology Seminar Series\, Dr. Kit Curtis
DESCRIPTION:Talk Title:  \nInference of field cancerization using stochastic models to improve cancer control \nTalk Summary:  \nEarly cancer detection strategies focus on screening individuals to find obvious precancerous lesions and removing them when possible. However\, screening programs often suffer from both under-diagnosis due to inadequate screening\, and over-diagnosis due to ineffective patient stratification in surveillance protocols. To overcome these shortcomings\, I will present mathematical methods that focus on detecting aspects of “field cancerization” to better define and target the dynamics of cancerized phenotypes evolving with age within the design of early detection strategies. Here we will incorporate various multiscale data\, ranging from population-level incidence to tissue-level (epi)genomic changes\, into stochastic models to understand the process of clonal evolution leading to malignancy in the gastrointestinal tract. I will present a novel molecular clock in Barrett’s esophagus to infer patient-specific Barrett’s onset age (a clinically unobservable event) based on changes in DNA methylation\, and end by discussing extensions of these methods to include additional tissue growth dynamics.
URL:https://componcmsk.org/event/computational-oncology-seminar-series-dr-kit-curtis/
LOCATION:Virtual
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=application/pdf:https://componcmsk.org/wp-content/uploads/2020/08/KCurtius-Dec-Talk-Flyer.pdf
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201110T100000
DTEND;TZID=America/New_York:20201110T110000
DTSTAMP:20260423T183712
CREATED:20200820T191027Z
LAST-MODIFIED:20201104T202749Z
UID:5413-1605002400-1605006000@componcmsk.org
SUMMARY:Computational Oncology Seminar Series\, Dr. Elaine Mardis
DESCRIPTION:Talk Title:  \nComputational Approaches for Genomics-Guided Pediatric Precision Cancer Medicine \nTalk Summary:  \nMy talk will focus on the methods and computational pipelines we are utilizing in molecular characterization of pediatric cancer patients with rare\, relapsed or treatment refractory cancers.  I will illustrate these approaches with specific case examples and a summary of our progress to-date. 
URL:https://componcmsk.org/event/computational-oncology-seminar-series-dr-elaine-mardis/
LOCATION:Virtual
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=application/pdf:https://componcmsk.org/wp-content/uploads/2020/08/EMardis-Event-Flyer-2020.pdf
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201020T100000
DTEND;TZID=America/New_York:20201020T110000
DTSTAMP:20260423T183712
CREATED:20200820T190901Z
LAST-MODIFIED:20201002T202120Z
UID:5409-1603188000-1603191600@componcmsk.org
SUMMARY:Computational Oncology Seminar Series\, Dr. Byron Wallace
DESCRIPTION:Talk Title:  \nLearning to summarize medical evidence \n \nTalk Summary:  \nDecisions about patient care should be supported by data. But most clinical evidence — from notes in electronic health records to published reports of clinical trials — is stored as unstructured text and so not readily accessible. The body of such unstructured evidence is already vast and continues to grow at breakneck pace. Physicians are overwhelmed by this torrent of data\, making it impossible to inform treatment decisions on the basis of all current relevant evidence. Natural language processing (NLP) methods offer a potential means of helping them make better use of this data to inform treatment decisions\, ultimately improving patient care. \n  \nIn this talk I will focus specifically on the task of generating summaries of evidence. I will consider two specific settings. In the first\, the aim is to design models that can synthesize all published evidence from randomized trials that addresses a particular clinical question; here the objective is to train a model to automatically generate such narrative synopses of the evidence. I will discuss challenges inherent to designing summarization models for this task\, including ensuring that summaries remain factual to the underlying content. The second setting concerns designing and training models that can provide extractive summaries of notes in patient electronic health record (EHR) data to aid radiologists performing imaging diagnosis. I will discuss the design and evaluation of a distantly supervised extractive summarization system that surfaces snippets from patient EHR that might support a given diagnostic query. \n 
URL:https://componcmsk.org/event/computational-oncology-seminar-series-dr-byron-wallace/
LOCATION:Virtual
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=application/pdf:https://componcmsk.org/wp-content/uploads/2020/08/BWallace-October-Talk-Flyer.pdf
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200922T110000
DTEND;TZID=America/New_York:20200922T120000
DTSTAMP:20260423T183712
CREATED:20200820T190648Z
LAST-MODIFIED:20200825T191413Z
UID:5407-1600772400-1600776000@componcmsk.org
SUMMARY:Computational Oncology Seminar Series\, Dr. Raphael Gottardo
DESCRIPTION:Talk Title:  \nEnabling the robust characterization of spatial gene expression architecture in tissue sections at increased resolution using Bayesian modeling \nTalk Summary:  \nNew single-cell technologies such as single-cell RNA-seq and high-dimensional flow cytometry enable the unprecedented interrogation of single-cell phenotypes (and functions) under various biological conditions. A common statistical problem is the discovery and characterization of such cell phenotypes from single-cell data and their relationship to clinical outcomes including response to cancer immunotherapy or protection after vaccination. More recently\, technological advances (e.g. Spatial Transcriptomics) have allowed for high-throughput profiling of gene expression while retaining spatial information bringing new computational challenges. During this talk\, I will present some statistical methodology we have developed to analyze spatial transcriptomic data and enhance the resolution of these data bringing us closer to single-cell resolution. I will illustrate these novel approaches using simulated data and several publicly available datasets that we have recently (re)analyzed to characterize the tumor microenvironment. \n 
URL:https://componcmsk.org/event/computational-oncology-seminar-series-dr-raphael-gottardo/
LOCATION:Virtual
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=application/pdf:https://componcmsk.org/wp-content/uploads/2020/08/RG-Talk-Flyer-September.pdf
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200617T100000
DTEND;TZID=America/New_York:20200617T110000
DTSTAMP:20260423T183712
CREATED:20200528T200436Z
LAST-MODIFIED:20200528T200929Z
UID:5222-1592388000-1592391600@componcmsk.org
SUMMARY:Computational Oncology Seminar Series\, Dr. Moritz Gerstung
DESCRIPTION:Talk Title:  \nCancer Data Science: Mutation\, Selection and Computation \nTalk Summary:  \nThe Gerstung lab develops statistical algorithms to learn more about the causes and consequences of cancer from large data sets. I will provide an overview about recent advances in the areas of cancer evolution\, mutational signature analysis\, as well as digital pathology and spatial genomics. Our analyses of the large cohort of cancer genomes assembled by the PCAWG consortium revealed that cancer driver mutations precede diagnosis by years to decades. These time scales are also observed in precancer data sets and provide a time frame within which transformation to malignant cancer can be predicted from genomic data. I’ll further present algorithms for learning intragenomic variation of mutational signatures and data from a large mutagenesis screen detailing how the interwoven and often counteracting forces of DNA damage\, tolerance and repair jointly sculpt mutational signatures. Lastly I’ll present some of the labs forays into digital pathology\, which reveal that a broad range of genomic and transcriptomic alterations are associated with histopathological characteristics which can be automatically learned with deep learning and subsequently localised within large tumor sections. Such observations are further corroborated by new spatial genomics and transcriptomics technologies that reveal subclonal growth patterns and their associated molecular and histopathological characteristics.
URL:https://componcmsk.org/event/computational-oncology-seminar-series-moritz-gerstung/
LOCATION:Virtual
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=application/pdf:https://componcmsk.org/wp-content/uploads/2020/05/Moritz-Ad.pdf
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200512T140000
DTEND;TZID=America/New_York:20200512T150000
DTSTAMP:20260423T183712
CREATED:20200501T180019Z
LAST-MODIFIED:20200528T200621Z
UID:5219-1589292000-1589295600@componcmsk.org
SUMMARY:Computational Oncology Seminar Series\, Dr. Hannah Carter
DESCRIPTION:Talk Title:  \nCoevolution of the cancer genome and MHC in immune surveillance by T cells \n  \nTalk Summary:  \nAntigen presentation via the Major Histocompatibility Complex Class (MHC) is an essential component of anti-tumor immunity induced by immune checkpoint inhibition. MHC molecules expose peptide fragments on the cell surface\, allowing T-Cell elimination of cells displaying antigen peptides. Although this system has evolved as a defense against microbial and viral agents\, MHC can also trigger elimination of cancerous cells harboring mutant peptides (neoantigens)\, a process is referred to as immune surveillance. The genomic region encoding the MHC is one of the most variable regions in the human population and each individual carries multiple MHC alleles that define the set of peptides that can be effectively presented for immune surveillance. We previously developed a computational framework to study interactions between inherited MHC genotypes and the mutational landscape of tumors. Studying these interactions across thousands of tumors in The Cancer Genome Atlas has revealed evidence that immune selection mediated through both class I and class II MHC molecules acts on tumors throughout their development. An inverse correlation between effective presentation and driver mutation frequency across tumor cohorts suggests that presentation is a key requirement for host immunity to control emerging tumor cell populations. Factors that impair the effectiveness of MHC presentation\, such as somatic alteration to the MHC itself\, are associated with an increase in neoantigen burden. These trends provide new clues about the limitations of endogenous antigen presentation that must be overcome to optimize patient responses to immune checkpoint blockade.
URL:https://componcmsk.org/event/computational-oncology-seminar-series-dr-hannah-carter/
LOCATION:Virtual
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=application/pdf:https://componcmsk.org/wp-content/uploads/2020/05/HCarter-Ad.pdf
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200430T140000
DTEND;TZID=America/New_York:20200430T150000
DTSTAMP:20260423T183712
CREATED:20200427T140031Z
LAST-MODIFIED:20200528T200719Z
UID:5215-1588255200-1588258800@componcmsk.org
SUMMARY:Computational Oncology Seminar Series\, Dr. CZ Zhang
DESCRIPTION:Talk Title: \nDynamic changes of unstable chromosomes: insights from in vitro genome evolution and cancer sequencing \n  \nTalk Summary:  \nCopy-number alterations and chromosomal translocations are widespread in cancer and frequently causing oncogenic mutations that drive tumorigenesis and therapy resistance. Despite their prevalence\, how these alterations arise during tumor development remains a mystery. We have gained significant insight into this question by two lines of research. In the first approach\, we analyzed genomic alterations induced by unstable chromosomes and their evolution over multiple generations by single-cell sequencing. We found that even a single broken chromosome in an ancestor cell can cause highly dynamic evolution and generate extensive genetic diversity in the progeny population\, giving rise to all forms of alterations in cancer genomes\, including focal amplification and deletion\, arm-level copy-number changes\, and complex rearrangements. This finding led us to hypothesize that the genetic diversity due to unstable chromosomes may fuel the transition from pre-malignancy to cancer. In the second approach\, we performed whole-genome sequencing on esophageal adenocarcinomas and matching precursor lesions from the same patients to track the evolution of chromosomal alterations during disease progression. The analysis of tumor genomes revealed a trajectory of genome evolution from benign to malignancy that bears a striking similarity to the evolution of unstable chromosomes in the in vitro experiments. Together\, our results suggest that a few simple mechanisms of chromosomal evolution may be sufficient to create the enormous complexity of cancer genomes and the evolution of unstable genomes may be not completely chaotic after all.
URL:https://componcmsk.org/event/computational-oncology-seminar-series-dr-cz-zhang/
LOCATION:Virtual
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=application/pdf:https://componcmsk.org/wp-content/uploads/2020/04/CZ-Zhang-Flyer.pdf
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200218T100000
DTEND;TZID=America/New_York:20200218T110000
DTSTAMP:20260423T183712
CREATED:20200212T211557Z
LAST-MODIFIED:20200212T211557Z
UID:5196-1582020000-1582023600@componcmsk.org
SUMMARY:Computational Oncology Seminar Series\, Dr. Claus T. Jensen
DESCRIPTION:Talk Title: \nDigital Transformation @ MSK \nTalk Summary: \nA discussion of digital transformation and what it means for MSK; focusing on digital vision and what we currently know about execution plans. The discussion will address both internal and external aspects of our journey\, as well as the opportunities and pitfalls involved. In particular we will cover how the ability to crunch more data\, with larger variety of source\, impact data driven research in general and computational oncology in particular. In all likelihood we are moving towards a cancer model where digital diagnostics and treatments become an integral part of a hybrid care model.
URL:https://componcmsk.org/event/computational-oncology-seminar-series-dr-claus-t-jensen/
LOCATION:Zuckerman Research Center Auditorium\, 417 E 68th Street\, New York\, NY\, 10065\, United States
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=application/pdf:https://componcmsk.org/wp-content/uploads/2020/02/Claus-Jensen-Lobby-Poster.pdf
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200128T100000
DTEND;TZID=America/New_York:20200128T110000
DTSTAMP:20260423T183712
CREATED:20200127T140003Z
LAST-MODIFIED:20200128T003218Z
UID:5179-1580205600-1580209200@componcmsk.org
SUMMARY:Computational Oncology Seminar Series\, Dr. Nicky McGranahan
DESCRIPTION:
URL:https://componcmsk.org/event/computational-oncology-seminar-series-dr-nicky-mcgranahan/
LOCATION:Zuckerman Research Center Auditorium\, 417 E 68th Street\, New York\, NY\, 10065\, United States
CATEGORIES:Seminar Series
ATTACH;FMTTYPE=image/png:https://componcmsk.org/wp-content/uploads/2020/01/Nicky-SS-Poster.png
END:VEVENT
END:VCALENDAR