Past Discussions


The date links to the discussion posts.  The title links to the article.

04/09/2018 –Using deep learning to model the hierarchical structure and function of a cell

03/26/2018 – FIND: difFerential chromatin INteractions Detection using a spatial Poisson process

03/12/2018 –Virtual ChIP-seq: predicting transcription factor binding by learning from the transcriptome

02/26/2018 –deepNF: Deep network fusion for protein function prediction

02/12/2018 –Clustering gene expression time series data using an infinite Gaussian process mixture model

01/29/2018 –NetSig: network-based discovery from cancer genomes

12/05/2017 –Learning causal networks with latent variables from multivariate information in genomic data.

11/07/2017 –Reconstruction of developmental landscapes by optimal-transport analysis of single-cell gene expression sheds light on cellular reprogramming.

10/24/2017 –Vicus: Exploiting local structures to improve network-based analysis of biological data.

10/10/2017 –Knowledge-guided gene prioritization reveals new insights into the mechanisms of chemoresistance.

09/26/2017 –Reversed graph embedding resolves complex single-cell trajectories.

09/12/2017GenomeDISCO: A concordance score for chromosome conformation capture experiments using random walks on contact map graphs

09/01/2017An Expanded View of Complex Traits: From Polygenic to Omnigenic

08/18/2017LASSIM—A network inference toolbox for genome-wide mechanistic modeling

08/04/2017Context Specificity in Causal Signaling Networks Revealed by Phosphoprotein Profiling

06/23/2017Visualization and analysis of single-cell RNA-seq data by kernel-based similarity learning

06/09/2017Predicting Causal Relationships from Biological Data: Applying Automated Casual Discovery on Mass Cytometry Data of Human Immune Cells

05/26/2017Selecting the most appropriate time points to profile in high-throughpsut studies

04/28/2017Discovering sparse transcription factor codes for cell states and state transitions during development

04/14/2017Can We Predict Gene Expression by Understanding Proximal Promoter Architecture?

03/24/2017 – Reproducibility of computational workflows is automated using continuous analysis

03/10/2017 – Genome-Scale Networks Link Neurodegenerative Disease Genes to α-Synuclein through Specific Molecular Pathways

02/24/2017 – Mutation effects predicted from sequence co-variation

02/10/2017 – Affinity regression predicts the recognition code of nucleic acid–binding proteins

01/27/2017 – Lineage-Specific Genome Architecture Links Enhancers and Non-coding Disease Variants to Target Gene Promoters

12/19/2016Compact Integration of Multi-Network Topology for Functional Analysis of Genes

12/05/2016Genome-scale high-resolution mapping of activating and repressive nucleotides in regulatory regions

11/21/2016DeepChrome: Deep-learning for predicting gene expression from histone modifications

10/10/2016Integrated Proteogenomic Characterization of Human High-Grade Serous Ovarian Cancer

9/26/2016Causal Mechanistic Regulatory Network for Glioblastoma Deciphered Using Systems Genetics Network Analysis

9/12/2016Context Specific and Differential Gene Co-expression Networks via Bayesian Biclustering

8/15/2016Tensor decomposition for multiple-tissue gene expression experiments

8/01/2016CellCODE: a robust latent variable approach to differential expression analysis for heterogeneous cell populations

7/18/2016Epigenomic Co-localization and Co-evolution Reveal a Key Role for 5hmC as a Communication Hub in the Chromatin Network of ESCs

6/20/2016Simultaneous Pathway Activity Inference and Gene Expression Analysis Using RNA Sequencing

6/6/2016Identification of High-Impact cis-Regulatory Mutations Using Transcription Factor Specific Random Forest Models

5/16/2016Predicting tissue specific transcription factor binding sites

5/2/2016Inferring causal molecular networks

4/18/2016Analysis of computational footprinting methods for DNase sequencing experiments

3/28/2016Multitask matrix completion for learning protein interactions across diseases

3/14/2016Factor graphs and the sum-product algorithm

2/22/2016 A joint model of regulatory and metabolic networks.

2/8/2016 GIM3E: condition specific models of cellular metabolism.

1/25/2016 Enhancer Evolution across 20 Mammalian Species.

12/7/2015 Early enhancer establishment and regulatory locus complexity shape transcriptional programs in hematopoietic differentiation.

11/23/2015 Single-cell transcriptional analysis to uncover regulatory circuits driving cell fate decisions in early mouse development.

11/9/2015 Quantro, a data-driven method for choosing data normalization approaches.

11/9/2015 Quantro, a data-driven method for choosing data normalization approaches.

10/26/2015 Tissue specific network analysis of 35 human tissues from the GETx Consortium

10/12/2015DeMAND – Network perturbation analysis

9/28/2015DeepSEA – Predicting effects of noncoding variants

08/31/15 – DeepBind – Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning.

08/31/15 – Deep Learning – an intro to prep for future meetings.

08/19/15 – Wanderlust with special guest Monacle

08/05/15 – Computational and analytical challenges in single-cell transcriptomics

7/22/15 – Lovell et al, 2015 | Proportionality: A Valid Alternative to Correlation for Relative Data

6/10/15The human transcriptome across tissues and individuals

5/13/2015 – Integrative clustering of multiple genomic data types using a joint latent variable model with application to breast and lung cancer subtype analysis

4/29/2015 – Leng et al (2015)  EBSeq-HMM: A Bayesian approach for identifying gene-expression changes in ordered RNA-seq experiments

4/15/2015 – Kundaje et al (2015) Integrative analysis of 111 reference human epigenomes.

3/18/2015 – DOUBLE HEADER:  Statistics requantitates the central dogma & Impact of regulatory variation from RNA to protein

2/18/2015 – Defining an essential transcription factor program for naïve pluripotency

1/21/2015CellNet: Network Biology Applied to Stem Cell Engineering

2/4/2015Conditional density-based analysis of T cell signaling in single-cell data

1/21/2015Dissecting Engineered Cell Types and Enhancing Cell Fate Conversion via CellNet

1/7/2015 (POSTPONED TO 1/8/15)- Conservation of trans-acting circuitry during mammalian regulatory evolution

12/10/2014 – Regression Analysis of Combined Gene Expression Regulation in Acute Myeloid Leukemia

11/26/2014 – Methods for time series analysis of RNA-seq data with application to human Th17 cell differentiation.

10/29/2014Wigwams: identifying gene modules co-regulated across multiple biological conditions

10/15/2014 – Automatic Parameter Learning for Multiple Network Alignment

10/1/2014A Family of Algorithms for Computing Consensus about Node State from Network Data

9/17/2014Inference of patient-specific pathway activities from multi-dimensional cancer genomics data using PARADIGM

9/3/2014 – Multiplatform Analysis of 12 Cancer Types Reveals Molecular Classification within and across Tissues of Origin

8/6/2014 – An Integrated Model of Multiple-Condition ChIP-Seq Data Reveals Predeterminants of Cdx2 Binding 

7/23/2014 – Predicting Dynamic Signaling Network Response under Unseen Perturbations
(a continuation of the discussion from 07.09.14)

6/25/2014 – Network-guided regression for detecting associations between DNA methylation and gene expression

6/11/2014A Validated Regulatory Network for Th17 Cell Specification

4/16/2014 – SPINE: a framework for signaling-regulatory pathway inference from cause-effect experiments

4/2/2014 – Network deconvolution as a general method to distinguish direct dependencies in networks 

2/19/2014  – Factor Graphs and the Sum-Product Algorithm

2/5/2014 and 1/22/2014 Perturbation Biology: Inferring Signaling Networks in Cellular Systems 

12/9/2013Differential expression in RNA-seq: A matter of depth

11/13/2013TREEGL: reverse engineering tree-evolving gene networks underlying developing biological lineages