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
CCB@RECOMB I
- Satellite registration
-
-
Session 1 - Genomics
I
-
- Poster session &
coffee
-
-
Session 2 -
Immunotherapy and other translational applications
-
- Marta Lukza (Keynote)
-
Friday April 20th
CCB@RECOMB II
-
Session 3 - Single
cell approaches
-
- Coffee break
-
-
Session 4 - Imaging
-
- Juan C. Caicedo
(Keynote)
-
- Lunch break
-
-
Session 5 -
Functional and systems biology
-
- Coffee break
-
-
Session 6 - Genomics
II
-
- Nuria Lopez-Bigas
(Keynote)
-
-
Opening reception + Registration
-
Session 1 – Genomics I
- Sorting cancer karyotypes using double-cut-and-joins, duplications and deletions
- Decrypting the evolution of somatic mutations in human cancers
- Inference of Allele and Clone-specific Copy-Number Aberrations in Tumor Samples
- Onctopus: Lineage-Based Subclonal Reconstruction
- Meltos: Multi-Sample Tumor Phylogeny Reconstruction for Structural Variants
Session 2 – Immunotherapy and other translational applications
- Genomic amplifications and distal 6q loss are novel markers for poor survival in high-risk neuroblastoma patients
- DCSR: Differential correlation across survival ranking
- CELLector: Genomics Guided Selection of Cancer in vitro Models
- Predicting cancer evolution from immune interactions
Session 3 – Single cell approaches
- Dhaka: Variational Autoencoder for Unmasking Tumor Heterogeneity from Single Cell Genomic Data
- Probabilistic inference of clonal gene expression through integration of RNA & DNA-seq at single-cell resolution
- Cardelino: clonal assignment of single cells with expressed mutations
- Inferring Cancer Progression from Single Cell Sequencing while allowing loss of mutations
Session 4 – Imaging
- Classification of tumor images using deep convolutional neural networks
- Exploring the association between pathology images and genomic data in cancer
- Variant impact phenotyping using deep morphological profiling
Session 5 – Functional and systems biology
- Stabilized Independent Component Analysis outperforms other methods in finding reproducible signals in tumoral transcriptomes
- ELMER 2.0: An R/Bioconductor package to reconstruct gene regulatory networks from DNA methylation and transcriptome profiles
- POSTIT: Multi-task learning to infer transcript isoform regulation from epi-genomics and transcriptomics data
- Comprehensive Alternative Splicing Analysis of 8,512 TCGA Donors
Session 6 – Genomics II
- Integrative Analysis of Diverse Transcriptomic Alterations to Identify Cancer-Relevant Genes Across 27 Histotypes
- Assessing the effect of germline and somatic mutation on gene expression changes in 1,188 human tumours
- Integrated single-nucleotide and structural variation signatures of DNA-repair deficient human cancers
- TensorSignatures: a multidimensional tensor factorization framework for extraction of mutational signatures
- Coding and non-coding cancer mutations
Keynote speakers
ICREA-Institue for Research in Biomedicine (IRB Barcelona), Barcelona, Spain
Title: “Coding and non-coding cancer mutations”
Mount Sinai, New York, USA
Title: “Predicting cancer evolution from immune interactions”
Broad Institute, Boston, USA
Title: “Variant impact phenotyping using deep morphological profiling”
Organizers
Moritz Gerstung, EMBL-EBI, Hinxton, UK
Valentina Boeva, Institut Cochin & Inserm, Paris, France