Presentations and Authors

Loading...

Presentations and Authors

recombsb
ricci
recombrg
dream2011

RICCI: RCB-IDIBELL. Conference on cancer informatics

Panel 1	Modelling the cis- and trans-effect of DNA copy number aberrations on gene expression levels (224). Wessel N. van Wieringen More information We model the cis- and trans-effect of DNA copy number aberrations on gene expression levels using high-throughput cancer data

Panel 2	Identification of features specific for cancer-associated mutations (80). Eduard Porta , Ana Maria Rojas , Ildefonso Cases More information Use of ontologies to identify sequence ontology terms associated to cancer-related mutations

Panel 3	Epistasis and more: detecting interactions in cancer (231). Ewa Szczurek , Martin Vingron More information We distinguish four different types of pairwise interactions between genes mutated in cancer. We discuss the means to identify and distinguish those interactions automatically from high-throughput data. Interactions: implication, mutual exclusivity, synth

Panel 4	GSVA - Gene Set Variation Analysis (148). Sonja Hänzelmann , Robert Castelo , Justin Guinney More information Gene Set Variation Analysis permits the assessment of variation of pathway activity across samples in a completely unsupervised manner and facilitates the generation of more flexible and sophisticated pathway models.

Panel 5	EVALUATION OF PUBLISHED PROGNOSIS GENE EXPRESSION SIGNATURES IN COLORECTAL CANCER (236). Rebeca Sanz-Pamplona , Antoni Berenguer , David Cordero , Jorge Cortés , Víctor Moreno More information Several CRC prognostic gene signatures have been described. The aim of this work is to test the capability of these signatures to predict patients’ outcome in a significant number of independent datasets.

Panel 6	Challenges of the Information Age: The Impact of False Discovery on Pathway Identification (271). Colin Rog , Mary Edgerton More information We investigate the amplification effect of using false-positive results from high throughput results to generate disease-relevant networks from pathways databases. Gene Expression, Pathways, Networks, Informatics, False Discovery, Cancer Informatics

Panel 7	Identification of drug-resistant patient subtypes on the base of found regulatory clusters (302). Ekaterina Kotelnikova , Mikhail Pyatnitskiy , Maria Shkrob , Nikolai Daraselia More information Cancer, patient stratification, personalized medicine, subtype, gene expression, pathway, cluster, cetuximab, colorectal cancer, CRC, SNEA, Sub-network enrichment analysis, key regulator, diagnosis, drug, biomarker, microarray, EGFR, TGFB, SMAD, epithelia

Panel 8	Machine learning analysis of steroid metabolomics data for the detection of malignancy in patients with adrenal (338). Michael Biehl , Petra Schneider , David J. Smith , Han Stiekema , Beverly A. Hughes , Angela A. Taylor More information .

7th ANNUAL::RECOMB Systems Biology

Panel 1	Reconstructing a tumor initiating cell associated molecular interaction network (172). Ramkumar Hariharan , Radhakrishna Pillai More information Characterizing the tumor initiating cell associated molecular interaction network to glean a systems level understanding of this phenotype including its tumorigenicity and invasiveness. Tumor initiating cells, cancer stem cells, breast carcinoma

Panel 2	Integrating protein interaction networks with experiment based quality scores (241). Martin Schaefer , Jean-Fred Fontaine , Arunachalam Vinayagam , Pablo Porras , Erich Wanker , Miguel Andrade-Navarro More information integrated protein-protein interaction (PPI) network database web frontend with evidence based confidence scoring scheme

Panel 3	The DNA Damage Response: Evolution of a Pathway (103). Aida Arcas , Ildefonso Cases , Ana M. Rojas More information We try to infer the emergence of the DNA Damage Response pathway by studying the evolutionary conservation of its components among taxa covering all the lineages.

Panel 4	LARGE DIFFERENCES IN TRANSCRIPTIONAL NETWORKS OF NORMAL AND TUMOR COLON CELLS (117). David Cordero , Xavier Solé , Elisabet Guinó , Rebeca Sanz-Pamplona , Antoni Berenguer , Víctor Moreno More information Transcriptional regulatory network, ARACNe, crc, colorectal, colon, cancer, TF, Transcription Factor,

Panel 5	A randomized Steiner tree approach for biomarker discovery and classification of breast cancer metastasis (137). Md Jamiul Jahid , Jianhua Ruan More information Breast Cancer, Biomarker, Metastasis, Steiner tree, Randomized Steiner Tree approach, Classification

Panel 6	Identifying Differential Transcript Models by ARH on RNA-Seq data (147). Axel Rasche , Ralf Herwig More information Differential splicing prediction, entropy, RNA-Seq, microarray, Affymetrix exon array, information theory, transcript model, Alternative Splicing

Panel 7	The modular nature of dendritic cell responses to fungi (274). Lisa Rizzetto , Luca Beltrame , Sonja Buschow , Carl Figdor , Gerold Schuler , Duccio Cavalieri More information a broadly applicable approach, which could be instrumental to reveal transcriptional and regulatory networks of immune cells upon pathogen recognition. Keywords: pathway analysis, transcriptional network, immune recognition, fungi

Panel 8	Patterns of cancer development and progression in the protein-protein interaction network (163). Jordi Serra , Miquel Àngel Pujana More information The study of proteins altered in breast cancer development and progression, and with specific treatments and perturbations, reveals specific topological patterns and robustness in the interactome network. Breast cancer; Complex networks; Topology;

Panel 9	GUILDify: A web server for phenotypic characterization of genes through biological data integration and network-based prioritization algorithms (181). Emre Guney , Javier Garcia Garcia , Baldo Oliva More information Topology based prioritazition of genes using integrated protein-protein interaction network. Guilt-by-association, candidate disease-gene prioritization, ppi network.

Panel 10	Analysis of Hedgehog/Gli Signaling and Regulatory Networks in Cancer (144). Hendrik Hache More information Analysis of Hedgehog/Gli Signaling and Regulatory Networks in Cancer. EGF GLI reverse engineering

Panel 11	Identification of protein complexes maintaining Oct4 expression in mouse ES cells (154). Weronika Sikora-Wohlfeld , Andreas Beyer More information The study aims at identifying protein complexes involved in the maintenance of Oct4 expression in mouse embryonic stem cells. The analysis integrates two genome-wide siRNA screens and orthogonal data. ES cells, siRNA, protein complexes

Panel 12	Improving Hypothesis Generation Using Gaggle-Linked Visual Analysis Tools: Exploring an Integrated Analysis of Hematopoietic Differentiation (260). Kieran Mace , Christopher Poultney , Aviv Madar , Richard Bonneau More information Gaggle Bioinformatics Sungear Cytoscape IGV Hypothesis Generation Visualization Analysis

Panel 13	Systems-level study of cancer genetic interactions (182). Nuria Bonifaci , Nazanin Karbalai , Bertram Müller-Myhsok , Miguel Angel Pujana More information we will present data aimed at predicting, evaluating and network-modeling breast cancer genetic interactions. predictions will be examined for their overlap with different types of gene/protein functional and molecular relationships across species.

Panel 14	PROTEIN INTERACTION NETWORKS TO CLASSIFY METABOLIC FEATURES OF METASTATIC CELLS (243). Rebeca Sanz-Pamplona , Naiara Santana , Claudia Nieva , Pablo Minguez , Monica Narro , Àngels Sierra More information The objective of this work is to define differentially expressed functions that drive the organ-specific growth of breast cancer metastasis by a protein-protein interaction network approach.

Panel 15	Statistics for clusters in gene expression data (256). Marta Luksza , Michael Lässig , Johannes Berg More information clustering significance analysis gene expression statistics

Panel 16	Modelling cell-specific response to interferon beta by different immune cell subtypes (290). Inna Pertsovskaya , Julio Saez-Rodriguez , Pablo Villoslada More information boolean networks, systems biology, T cells, macrophages, CNopt, phosphoprotien analysis, cytokine response

Panel 17	Improved Time Complexities for Learning Boolean Networks (293). Yun Zheng More information We mathematically prove Boolean networks whose variables are related with OR/AND logic can be learned with the worst case complexity of O((N+logn)n^2). Boolean networks, systems biology, learning, algorithm

Panel 18	A drug-target interaction network enables inference of adverse cardiovascular events of non-cardiovascular drugs (297). Francisco Azuaje , Lulu Zhang , Yvan Devaux , Daniel Wagner More information Application of the analysis of a drug-target interaction network to identify cardiac adverse effetcs of non-cardiovascular drugs. Keywords: systems biology, translational systems biomedicine, drug-target interactions, cardiovascular drugs

Panel 19	Different transcript segments reveal consistent information about expression ratios in RNA-seq (323). Mei-Ju Chen , Chia-Cheng Hu , Ju-Chun Hsu , Chien-Yu Chen More information RNA-seq, gene expression, differential genes

Panel 20	Inference in transcriptional network motifs (343). Andrea Ocone , Guido Sanguinetti More information .

8th ANNUAL::RECOMB Regulatory Genomics

Panel 1	Analysis of DNA word distributions in four yeast genomes using a novel statistical background model (140). Ramkumar Hariharan , Regi Simon , Radhakrishna M Pillai , Todd D Taylor More information Anlaysis of k-mer distributions in genomic sequences from a set of realted species can reveal several biological insights beyond the mere identification of regulatory elements. k-mers, genomes, over-representation, conservation

Panel 2	Unified, optimal framework for integrative Next-Gen sequence analysis (205). Vibhor Kumar , Masafumi Muratani , Nirmala Rayan , Huck Hui Ng , Shyam Prabhakar More information New, unified and provably optimal framework for integrative Next-Gen sequence analysis outperforms customized methods and reveals novel insights into the relationships between genome-wide functional datasets. Regulatory Genomics.

Panel 3	Toward a Functional Map of splicing-related genes in C. elegans: from functional genomics of the SM-like family to genetic analysis of lsm-1 (122). Eric Cornes , Julián Ceron More information Study the alternative functions of splicing-related genes in C. elegans. Genetic and genomic tools. Phenome. Localizome. Interactome. Functional network. Spliceosome. RNA metabolism. lsm family.

Panel 4	A multifactorial integrative analysis scheme for combined microRNA and gene expression datasets (75). Alain Sewer , Arnd Hengstermann , Vincenzo Belcastro , Carole Mathis , Julia Hoeng More information Combined microRNA and gene expression data are analyzed in terms of the factors of the underlying experiment. This approach provides a powerful filter for identifying the relevant regulatory relationships.

Panel 5	Global analysis of Polycomb and histone modifying enzymes misregulation in cancer (119). Alba Jene-Sanz , Nuria Lopez-Bigas More information Regulatory pathways in cancer. Survival analysis. Polycomb, hmt, hdm, hdac, hat, histone modifications

Panel 6	Tumor Adaptation and Signal Rewiring after Anti-Angiogenic Therapies in Renal Cell Carcinoma (150). Lidia Moserle , Gabriela Jiménez , Mar Martínez , August Vidal , Francesc Vinyals , Oriol Casanovas More information Therapeutic Resistance and Tumor Adaptation to Anti-Angiogenic Therapies in Mouse Models of Cancer

Panel 7	Integrative Biclustering of DNAse hypersensitivity and binding site information for learning conserved co-regulated groups active during hematopoietic stem cells differentiation (257). Francis F. Kirigin , Peter Waltman , Thadeous Kacmarczyk , Kieran Mace , Richard Bonneau More information Integrative biclustering of regulatory elements for t-cell differentiation in hematopoietic stem cell lines, Gene regulation, Genome annotation, Genome characterization

Panel 8	Bioinformatics and personalized medicine: Training, methods and bioinformatics tools for clinical genomics (333). Allan Orozco More information Methodology and applied bioinformatics tools, on the formation of the translational bioinformatics. proposed to improve the diverse genomic information analysis coming from the clinical hospital patient.

Panel 9	Investigating links between primary structure of AP2/ERF family and the target DNA sequences (314). Yi-An Tung , Hsing-Yu Chen , Tsan-Piao Lin , Chien-Yu Chen More information targets of AP2/ERF family

Panel 10	Amadeus-PBM: Fast and accurate motif discovery from protein binding microarray data (305). Yaron Orenstein , Chaim Linhart , Ron Shamir More information de novo Motif finding protein binding microarray Amadeus cis-regulation

Panel 11	Discovery of cancer regulators for co-expressed human genes using large sequence search spaces (319). Rekin's Janky , Bram Van de Sande , Zeynep Kalender Atak , Stein Aerts More information regulatory network, cancer, motif discovery, CisTargetX, gene signature, expression data, microarray, regulatory modules, human, conservation, transcription factor, enhancers, validation

Panel 12	A computational pipeline to discover highly phylogenetically informative genes in sequenced genomes: application to S. cerevisiae natural strains (344). Mateo Ramazzotti , Luisa Berná , Irene Stefanini , Duccio Cavalieri More information .

Panel 13	Chromatin Marks Identify Two Distinct Regulatory Classes of Female-specific, Growth Hormone-regulated Genes in Mouse Liver (164). Aarathi Sugathan , Ekaterina Laz , Andy Rampersaud , David Waxman More information ChIP-Seq analysis of H3K27me3, H3K4me1, and H3K4me3 in mouse liver reveals sexually dimorphic chromatin patterns that mark two distinct classes of female-specific, growth hormone-regulated genes.

6th ANNUAL-DREAM::Engineering Challenges

Panel 1	NetworkInference.org – A community platform for gene network inference (347). Daniel Marbach , Gustavo Stolovitzky , Andrea Califano , Manolis Kellis More information Network inference, gene regulatory networks, open-source platform, toolkit

Panel 2	Logistic Regression for AML Prediction (93). Tapio Manninen , Heikki Huttunen , Pekka Ruusuvuori , Matti Nykter More information We describe our submission for the DREAM6/FlowCAP2 molecular classification of acute myeloid leukemia (AML) challenge. AML, diagnosis, classification, machine learning, logistic regression, LDA, LASSO

Panel 3	Multi-level determination of confidence scores for alternatively spliced mRNA transcripts discovered by de novo assembler (320). Ting-Ying Chien , Mei-Ju May Chen , Chien-Yu Chen More information de novo assembly, motif matching approach

Panel 4	Admire-LVQ: Analysis of Flow Cytometry Data by Matrix Relevance Learning Vector Quantization (337). Michael Biehl , Kerstin Bunte , Petra Schneider More information .

Panel 5	Regression based classification of AML flow cytometry profiles (339). David Amar , Yaron Orenstein , Ron Zeira , Ron Shamir More information .

Panel 6	eMASH6: from promoter sequences to gene expression (345). Ewa Szczurek , Alena Myšičková , Martin Vingron , Holger Klein , Szymon M. Kielbasa More information .