Dates: 19-20 April, 2018

RECOMB-Computational Cancer Biology (CCB) focuses on applying statistical, mathematical, and algorithmic approaches to improve our understanding of cancer and on the development of useful, effective and efficient new methods in this area.

This year, RECOMB-CCB is going to precede the main RECOMB conference.

Special interest topics

  • Genomics, transcriptomics and epigenetics
  • Immunotherapy and other translational applications
  • Imaging
  • Functional and systems biology
  • Single cell approaches

Program and abstract book

Download the program and the abstract book here.

Schedule at-a-glance

Thursday April 19th

Friday April 20th

Session 1 – Genomics I

  • Ron ZeiraSorting cancer karyotypes using double-cut-and-joins, duplications and deletions
  • Santiago GonzalezDecrypting the evolution of somatic mutations in human cancers
  • Simone ZaccariaInference of Allele and Clone-specific Copy-Number Aberrations in Tumor Samples
  • Linda SundermanOnctopus: Lineage-Based Subclonal Reconstruction
  • Camir RickettsMeltos: Multi-Sample Tumor Phylogeny Reconstruction for Structural Variants

Session 2 – Immunotherapy and other translational applications

  • Pauline DepuydtGenomic amplifications and distal 6q loss are novel markers for poor survival in high-risk neuroblastoma patients
  • Shila GhazanfarDCSR: Differential correlation across survival ranking
  • Hanna NajgebauerCELLector: Genomics Guided Selection of Cancer in vitro Models
  • Marta Łuksza (Keynote)Predicting cancer evolution from immune interactions

Session 3 – Single cell approaches

  • Sabrina RashidDhaka: Variational Autoencoder for Unmasking Tumor Heterogeneity from Single Cell Genomic Data
  • Kieran CampbellProbabilistic inference of clonal gene expression through integration of RNA & DNA-seq at single-cell resolution
  • Yuanhua Huang.Cardelino: clonal assignment of single cells with expressed mutations
  • Simone CiccolellaInferring Cancer Progression from Single Cell Sequencing while allowing loss of mutations

Session 4 – Imaging

  • Iman HajirasoulihaClassification of tumor images using deep convolutional neural networks
  • Yu FuExploring the association between pathology images and genomic data in cancer
  • Juan Caicedo (Keynote)Variant impact phenotyping using deep morphological profiling

Session 5 – Functional and systems biology

  • Laura CantiniStabilized Independent Component Analysis outperforms other methods in finding reproducible signals in tumoral transcriptomes
  • Tiago SilvaELMER 2.0: An R/Bioconductor package to reconstruct gene regulatory networks from DNA methylation and transcriptome profiles
  • Azim Dehghani AmirabadPOSTIT: Multi-task learning to infer transcript isoform regulation from epi-genomics and transcriptomics data
  • Andre KahlesComprehensive Alternative Splicing Analysis of 8,512 TCGA Donors

Session 6 – Genomics II

  • Natalie DavidsonIntegrative Analysis of Diverse Transcriptomic Alterations to Identify Cancer-Relevant Genes Across 27 Histotypes
  • Kjong LehmannAssessing the effect of germline and somatic mutation on gene expression changes in 1,188 human tumours
  • Tyler FunnellIntegrated single-nucleotide and structural variation signatures of DNA-repair deficient human cancers
  • Harald VoehringerTensorSignatures: a multidimensional tensor factorization framework for extraction of mutational signatures
  • Nuria Lopez-Bigaz (Keynote)Coding and non-coding cancer mutations

Keynote speakers

Nuria Lopez-Bigas

ICREA-Institue for Research in Biomedicine (IRB Barcelona), Barcelona, Spain

Title: “Coding and non-coding cancer mutations


Marta Łuksza

Mount Sinai, New York, USA

Title: “Predicting cancer evolution from immune interactions

Juan Caicedo

Broad Institute, Boston, USA

Title: “Variant impact phenotyping using deep morphological profiling



Moritz Gerstung, EMBL-EBI, Hinxton, UK
Valentina Boeva, Institut Cochin & Inserm, Paris, France