Static properties of transcription factors (TFs) within the hierarchical framework. Static properties of transcription factors (TFs) within the hierarchical.

Slides:



Advertisements
Similar presentations
Genomic analysis of regulatory network dynamics reveals large topological changes Paper Study Speaker: Cai Chunhui Sep 21, 2004.
Advertisements

Regulatory networks 10/29/07. Definition of a module Module here has broader meanings than before. A functional module is a discrete entity whose function.
Li Chen 4/3/2009 CSc 8910 Analysis of Biological Network, Spring 2009 Dr. Yi Pan.
Constructing and Analyzing a Gene Regulatory Network Siobhan Brady UC Davis.
Network Motifs See some examples of motifs and their functionality Discuss a study that showed how a miRNA also can be integrated into motifs Today’s plan.
Change in Pufs and their RNA InteractionsAnalogous change in transcription factors and their gene regulation Puf binding specificity tends to be conserved.
Hyunghoon Cho, Bonnie Berger, Jian Peng  Cell Systems 
DNase‐HS sites are main independent determinants of DNA replication timing Simulations based on genome sequence features (GC content, CpG islands), or.
Principles of using neural networks for predicting molecular traits from DNA sequence Principles of using neural networks for predicting molecular traits.
Statistical analysis of the influence of network regulators on topology clusters in the oleate network. Statistical analysis of the influence of network.
Network topology reflects target gene expression profile and function.
Inferred dynamic model of transcriptional regulatory network.
Analysis of mutational effects of parameters on the phenotype (i. e
Hnf4g importance in human colon cancer organoids and regulation of the Hnf4a locus Hnf4g importance in human colon cancer organoids and regulation of the.
(A) Graph depicting interaction between the five regulatory motifs measured by synergy and cooccurrence. (A) Graph depicting interaction between the five.
Sensitivity of RNA‐seq.
Analysis of in silico flux changes along the exponential growth phase: (A) In silico flux changes from 24 to 36 h, from 36 to 48 h, and from 48 to 60 h.
Illustration of the reactions and metabolites obtained from random sampling. Illustration of the reactions and metabolites obtained from random sampling.
Motif detectability corresponds to the phylogenetic profile of the cognate transcription factor. Motif detectability corresponds to the phylogenetic profile.
Activity flow of the mTOR signaling network.
Heatmaps of the gene mutation distributions in oncogene‐signaling blocks for six representative cancer types. Heatmaps of the gene mutation distributions.
Exo‐metabolomics profiling of major metabolites elucidated the metabolic capabilities of monospecies Exo‐metabolomics profiling of major metabolites elucidated.
Predicted and measured double‐ring formation.
Proteins with hotspot mutations are often in the interaction networks with known cancer driver proteins Proteins with hotspot mutations are often in the.
(C–F) Complete interaction networks (representing both baits and preys) for selected groups of baits. (C–F) Complete interaction networks (representing.
Highly correlating interaction profiles can predict functional similarity Highly correlating interaction profiles can predict functional similarity AROC.
Splicing changes in development and aging.
Buffering of non‐functional mRNA co‐regulation likely is a passive process Buffering of non‐functional mRNA co‐regulation likely is a passive process Percentage.
Spatial proximity of genes affects mRNA but not protein regulation
Coupling immunophenotypes to Drop‐seq data
Characterization of promoters relative to pAGA1
Modelling Structure and Function in Complex Networks
Hierarchical structure in the yeast transcription regulatory network.
Impulse Control: Temporal Dynamics in Gene Transcription
Marker reproducibility and metastasis prediction performance.
Widespread modulation of epigenetic landscape for differentiated organoids is driven by Hnf4g Widespread modulation of epigenetic landscape for differentiated.
A coherent feed‐forward motif sharpens the Dnmt3b transcriptional output into a bistable switch. A coherent feed‐forward motif sharpens the Dnmt3b transcriptional.
Heat maps showing global relative growth phenotype and comparison between measured and predicted values. Heat maps showing global relative growth phenotype.
Direct dFOXO targets in wild‐type adult flies.
The transcript profiles in the three human cell lines based on RNA sequencing (RNA‐seq). The transcript profiles in the three human cell lines based on.
Properties of proteins and residues with frequent hotspot mutations
Neurogenins induce a network of transcription factors that mediate iNGN neurogenesisA network of transcription factors involved in iNGN neurogenesis was.
Francis Crick's central dogma of biology revolves around the transcription of mRNA from DNA, the translation of proteins from mRNA, and the degradation.
Recursive construction and error correction of a simple combinatorial library. Recursive construction and error correction of a simple combinatorial library.
Volume 132, Issue 6, Pages (March 2008)
Comparison of proteomics and RNA‐Seq data.
Characteristics of tissue‐specific co‐expression networks (CNs)‏
Determination of mRNA synthesis and decay rates.
Predicting Gene Expression from Sequence
Volume 35, Issue 2, Pages (August 2011)
An integrated NHR network.
Design and optimization of the computational model.
Subnetworks enriched for the hallmarks of cancer.
Network modules correspond to known and novel functional distinctions between neuronal subtypes. Network modules correspond to known and novel functional.
RSLs enable internal replicate and lineage dropout analyses
Stage‐dependent diurnal transcript changes.
Example transcript and protein patterns.
Distinct collagen structures in the upper and lower neonatal dermis (related to Fig 1)‏ Distinct collagen structures in the upper and lower neonatal dermis.
Cluster analysis of all identified models.
Antisense‐mediated regulation of SUR7.
Characterising dermis expansion and gene expression changes during mouse development (related to Fig 1)‏ Characterising dermis expansion and gene expression.
Antisense expression associates with larger gene expression variability. Antisense expression associates with larger gene expression variability. (A–D)
Global and focused views of human interaction map.
Patterns and regulation of age‐related splicing changes.
Functional metabolic rearrangements in chloramphenicol‐resistant populations Functional metabolic rearrangements in chloramphenicol‐resistant populations.
Dynamic regulatory map and static network for yeast response to AA starvation. Dynamic regulatory map and static network for yeast response to AA starvation.
Integration of proteomic data into the model
Mouse Y1H pipeline. Mouse Y1H pipeline. (A) Workflow to retrieve the mouse TF open‐reading frame (ORF) clone resource. We predict that the mouse genome.
Hyunghoon Cho, Bonnie Berger, Jian Peng  Cell Systems 
Inferred promoter–metabolite regulation network (Table EV7)
Presentation transcript:

Static properties of transcription factors (TFs) within the hierarchical framework. Static properties of transcription factors (TFs) within the hierarchical framework. (A) Average number of target genes (TGs) regulated or co‐regulated by TFs (left), percentage of TFs in each layer that are hubs (middle), and degree distribution of TFs (right). (B) Break‐down of combinatorial regulatory patterns from a TG's perspective showing the percentage of TGs regulated by a combinatorial set of TFs from one or more layers. Less than 1% of TGs are jointly regulated by the top‐ and bottom‐layer TFs. Values marked with red and green texts and arrows indicate that the corresponding subgroups are statistically under‐ or over‐represented, respectively, compared with those in random networks of same size and degree distribution as the yeast regulatory network (see Results and Materials and methods). The percentages do not add up to 100, as a small fraction of genes are regulated by the ten unclassified TFs not included in the study. (C) Break‐down of feed‐forward loop (FFL) motifs showing the composition of all FFL motifs in the yeast regulatory network. Top panel shows FFL motifs where all the three nodes involve TFs, and the bottom panel shows FFL motifs involving two TFs and a TG. About 94% of all FFL motifs involve only the core‐ and/or top‐layer TFs. Statistically over‐represented FFL patterns are indicated by a green arrow, P<1.6 × 10−3. The percentages do not add up to 100, as a small fraction of genes are regulated by the ten unclassified TFs not included in the study. (D) Percentages of TFs that are essential in each of the three layers of the hierarchy. (E) Distribution of TF conservation levels (presence/absence of orthologs) across 15 fungal genomes in each of the three layers of the hierarchy. (F) Distribution of number of gene ontology (GO) biological processes a TF is associated with. Raja Jothi et al. Mol Syst Biol 2009;5:294 © as stated in the article, figure or figure legend