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1.  The Biological Connection Markup Language: a SBGN-compliant format for visualization, filtering and analysis of biological pathways 
Bioinformatics  2011;27(15):2127-2133.
Motivation: Many models and analysis of signaling pathways have been proposed. However, neither of them takes into account that a biological pathway is not a fixed system, but instead it depends on the organism, tissue and cell type as well as on physiological, pathological and experimental conditions.
Results: The Biological Connection Markup Language (BCML) is a format to describe, annotate and visualize pathways. BCML is able to store multiple information, permitting a selective view of the pathway as it exists and/or behave in specific organisms, tissues and cells. Furthermore, BCML can be automatically converted into data formats suitable for analysis and into a fully SBGN-compliant graphical representation, making it an important tool that can be used by both computational biologists and ‘wet lab’ scientists.
Availability and implementation: The XML schema and the BCML software suite are freely available under the LGPL for download at http://bcml.dc-atlas.net. They are implemented in Java and supported on MS Windows, Linux and OS X.
Contact: duccio.cavalieri@unifi.it; sorin@wayne.edu
Supplementary information: Supplementary data are available at Bioinformatics online.
doi:10.1093/bioinformatics/btr339
PMCID: PMC3137220  PMID: 21653523
2.  Nuclear Receptor Signaling Atlas (): hyperlinking the nuclear receptor signaling community 
Nucleic Acids Research  2005;34(Database issue):D221-D226.
The nuclear receptor signaling (NRS) field has generated a substantial body of information on nuclear receptors, their ligands and coregulators, with the ultimate goal of constructing coherent models of the biological and clinical significance of these molecules. As a component of the Nuclear Receptor Signaling Atlas (NURSA)—the development of a functional atlas of nuclear receptor biology—the NURSA Bioinformatics Resource is developing a strategy to organize and integrate legacy and future information on these molecules in a single web-based resource (). This entails parallel efforts of (i) developing an appropriate software framework for handling datasets from NURSA laboratories and (ii) designing strategies for the curation and presentation of public data relevant to NRS. To illustrate our approach, we have described here in detail the development of a web-based interface for the NURSA quantitative PCR nuclear receptor expression dataset, incorporating bioinformatics analysis which provides novel perspectives on functional relationships between these molecules. We anticipate that the free and open access of the community to a platform for data mining and hypothesis generation strategies will be a significant contribution to the progress of research in this field.
doi:10.1093/nar/gkj029
PMCID: PMC1347392  PMID: 16381851
3.  Atlas of Gene Expression in the Developing Kidney at Microanatomic Resolution 
Developmental cell  2008;15(5):781-791.
Summary
Kidney development is based on differential cell type specific expression of a vast number of genes. While multiple critical genes and pathways have been elucidated, a genomewide analysis of gene expression within individual cellular and anatomic structures is lacking. Accomplishing this could provide significant new insights into fundamental developmental mechanisms such as mesenchymal-epithelial transition, inductive signaling, branching morphogenesis and segmentation. We describe here a comprehensive gene expression atlas of the developing mouse kidney based on the isolation of each major compartment by either laser capture microdissection or fluorescent activated cell sorting, followed by microarray profiling. The resulting data agrees with known expression patterns and additional in situ hybridizations. This kidney atlas allows a comprehensive analysis of the progression of gene expression states during nephrogenesis, as well as discovery of novel growth factor-receptor interactions. In addition, the results provide deeper insight into the genetic regulatory mechanisms of kidney development.
doi:10.1016/j.devcel.2008.09.007
PMCID: PMC2653061  PMID: 19000842
4.  A HaemAtlas: characterizing gene expression in differentiated human blood cells 
Blood  2009;113(19):e1-e9.
Hematopoiesis is a carefully controlled process that is regulated by complex networks of transcription factors that are, in part, controlled by signals resulting from ligand binding to cell-surface receptors. To further understand hematopoiesis, we have compared gene expression profiles of human erythroblasts, megakaryocytes, B cells, cytotoxic and helper T cells, natural killer cells, granulocytes, and monocytes using whole genome microarrays. A bioinformatics analysis of these data was performed focusing on transcription factors, immunoglobulin superfamily members, and lineage-specific transcripts. We observed that the numbers of lineage-specific genes varies by 2 orders of magnitude, ranging from 5 for cytotoxic T cells to 878 for granulocytes. In addition, we have identified novel coexpression patterns for key transcription factors involved in hematopoiesis (eg, GATA3-GFI1 and GATA2-KLF1). This study represents the most comprehensive analysis of gene expression in hematopoietic cells to date and has identified genes that play key roles in lineage commitment and cell function. The data, which are freely accessible, will be invaluable for future studies on hematopoiesis and the role of specific genes and will also aid the understanding of the recent genome-wide association studies.
doi:10.1182/blood-2008-06-162958
PMCID: PMC2680378  PMID: 19228925
5.  GPX-Macrophage Expression Atlas: A database for expression profiles of macrophages challenged with a variety of pro-inflammatory, anti-inflammatory, benign and pathogen insults 
BMC Genomics  2005;6:178.
Background
Macrophages play an integral role in the host immune system, bridging innate and adaptive immunity. As such, they are finely attuned to extracellular and intracellular stimuli and respond by rapidly initiating multiple signalling cascades with diverse effector functions. The macrophage cell is therefore an experimentally and clinically amenable biological system for the mapping of biological pathways. The goal of the macrophage expression atlas is to systematically investigate the pathway biology and interaction network of macrophages challenged with a variety of insults, in particular via infection and activation with key inflammatory mediators. As an important first step towards this we present a single searchable database resource containing high-throughput macrophage gene expression studies.
Description
The GPX Macrophage Expression Atlas (GPX-MEA) is an online resource for gene expression based studies of a range of macrophage cell types following treatment with pathogens and immune modulators. GPX-MEA follows the MIAME standard and includes an objective quality score with each experiment. It places special emphasis on rigorously capturing the experimental design and enables the searching of expression data from different microarray experiments. Studies may be queried on the basis of experimental parameters, sample information and quality assessment score. The ability to compare the expression values of individual genes across multiple experiments is provided. In addition, the database offers access to experimental annotation and analysis files and includes experiments and raw data previously unavailable to the research community.
Conclusion
GPX-MEA is the first example of a quality scored gene expression database focussed on a macrophage cellular system that allows efficient identification of transcriptional patterns. The resource will provide novel insights into the phenotypic response of macrophages to a variety of benign, inflammatory, and pathogen insults. GPX-MEA is available through the GPX website at .
doi:10.1186/1471-2164-6-178
PMCID: PMC1351201  PMID: 16343346
6.  Pathway Projector: Web-Based Zoomable Pathway Browser Using KEGG Atlas and Google Maps API 
PLoS ONE  2009;4(11):e7710.
Background
Biochemical pathways provide an essential context for understanding comprehensive experimental data and the systematic workings of a cell. Therefore, the availability of online pathway browsers will facilitate post-genomic research, just as genome browsers have contributed to genomics. Many pathway maps have been provided online as part of public pathway databases. Most of these maps, however, function as the gateway interface to a specific database, and the comprehensiveness of their represented entities, data mapping capabilities, and user interfaces are not always sufficient for generic usage.
Methodology/Principal Findings
We have identified five central requirements for a pathway browser: (1) availability of large integrated maps showing genes, enzymes, and metabolites; (2) comprehensive search features and data access; (3) data mapping for transcriptomic, proteomic, and metabolomic experiments, as well as the ability to edit and annotate pathway maps; (4) easy exchange of pathway data; and (5) intuitive user experience without the requirement for installation and regular maintenance. According to these requirements, we have evaluated existing pathway databases and tools and implemented a web-based pathway browser named Pathway Projector as a solution.
Conclusions/Significance
Pathway Projector provides integrated pathway maps that are based upon the KEGG Atlas, with the addition of nodes for genes and enzymes, and is implemented as a scalable, zoomable map utilizing the Google Maps API. Users can search pathway-related data using keywords, molecular weights, nucleotide sequences, and amino acid sequences, or as possible routes between compounds. In addition, experimental data from transcriptomic, proteomic, and metabolomic analyses can be readily mapped. Pathway Projector is freely available for academic users at http://www.g-language.org/PathwayProjector/.
doi:10.1371/journal.pone.0007710
PMCID: PMC2770834  PMID: 19907644
7.  An expression atlas of human primary cells: inference of gene function from coexpression networks 
BMC Genomics  2013;14:632.
Background
The specialisation of mammalian cells in time and space requires genes associated with specific pathways and functions to be co-ordinately expressed. Here we have combined a large number of publically available microarray datasets derived from human primary cells and analysed large correlation graphs of these data.
Results
Using the network analysis tool BioLayout Express3D we identify robust co-associations of genes expressed in a wide variety of cell lineages. We discuss the biological significance of a number of these associations, in particular the coexpression of key transcription factors with the genes that they are likely to control.
Conclusions
We consider the regulation of genes in human primary cells and specifically in the human mononuclear phagocyte system. Of particular note is the fact that these data do not support the identity of putative markers of antigen-presenting dendritic cells, nor classification of M1 and M2 activation states, a current subject of debate within immunological field. We have provided this data resource on the BioGPS web site (http://biogps.org/dataset/2429/primary-cell-atlas/) and on macrophages.com (http://www.macrophages.com/hu-cell-atlas).
doi:10.1186/1471-2164-14-632
PMCID: PMC3849585  PMID: 24053356
Clustering; Meta-analysis; Human; Primary cells; Dendritic cell; Macrophage; Microarray; Transcriptomics
8.  Atlas of Signaling for Interpretation of Microarray Experiments 
PLoS ONE  2010;5(2):e9256.
Microarray-based expression profiling of living systems is a quick and inexpensive method to obtain insights into the nature of various diseases and phenotypes. A typical microarray profile can yield hundreds or even thousands of differentially expressed genes and finding biologically plausible themes or regulatory mechanisms underlying these changes is a non-trivial and daunting task. We describe a novel approach for systems-level interpretation of microarray expression data using a manually constructed “overview” pathway depicting the main cellular signaling channels (Atlas of Signaling). Currently, the developed pathway focuses on signal transduction from surface receptors to transcription factors and further transcriptional regulation of cellular “workhorse” proteins. We show how the constructed Atlas of Signaling in combination with an enrichment analysis algorithm allows quick identification and visualization of the main signaling cascades and cellular processes affected in a gene expression profiling experiment. We validate our approach using several publicly available gene expression datasets.
doi:10.1371/journal.pone.0009256
PMCID: PMC2822851  PMID: 20174649
9.  An Atlas of the Epstein-Barr Virus Transcriptome and Epigenome Reveals Host-Virus Regulatory Interactions 
Cell host & microbe  2012;12(2):233-245.
Epstein-Barr Virus (EBV), which is associated with multiple human tumors, persists as a minichromosome in the nucleus of B-lymphocytes and induces malignancies through incompletely understood mechanisms. Here, we present a large-scale functional genomic analysis of EBV. Our experimentally generated nucleosome positioning maps and viral protein binding data were integrated with over 700 publicly available high-throughput sequencing data sets for human lymphoblastoid cell lines mapped to the EBV genome. We found that viral lytic genes are coexpressed with cellular cancer-associated pathways, suggesting that the lytic cycle may play an unexpected role in virus-mediated oncogenesis. Host regulators of viral oncogene expression and chromosome structure were identified and validated, revealing a role for the B-cell-specific protein Pax5 in viral gene regulation and the cohesin complex in regulating higher order chromatin structure. Our findings provide a deeper understanding of latent viral persistence in oncogenesis and establish a valuable viral genomics resource for future exploration.
doi:10.1016/j.chom.2012.06.008
PMCID: PMC3424516  PMID: 22901543
10.  A gene expression atlas of the domestic pig 
BMC Biology  2012;10:90.
Background
This work describes the first genome-wide analysis of the transcriptional landscape of the pig. A new porcine Affymetrix expression array was designed in order to provide comprehensive coverage of the known pig transcriptome. The new array was used to generate a genome-wide expression atlas of pig tissues derived from 62 tissue/cell types. These data were subjected to network correlation analysis and clustering.
Results
The analysis presented here provides a detailed functional clustering of the pig transcriptome where transcripts are grouped according to their expression pattern, so one can infer the function of an uncharacterized gene from the company it keeps and the locations in which it is expressed. We describe the overall transcriptional signatures present in the tissue atlas, where possible assigning those signatures to specific cell populations or pathways. In particular, we discuss the expression signatures associated with the gastrointestinal tract, an organ that was sampled at 15 sites along its length and whose biology in the pig is similar to human. We identify sets of genes that define specialized cellular compartments and region-specific digestive functions. Finally, we performed a network analysis of the transcription factors expressed in the gastrointestinal tract and demonstrate how they sub-divide into functional groups that may control cellular gastrointestinal development.
Conclusions
As an important livestock animal with a physiology that is more similar than mouse to man, we provide a major new resource for understanding gene expression with respect to the known physiology of mammalian tissues and cells. The data and analyses are available on the websites http://biogps.org and http://www.macrophages.com/pig-atlas.
doi:10.1186/1741-7007-10-90
PMCID: PMC3814290  PMID: 23153189
pig; porcine; Sus scrofa; microarray; transcriptome; transcription network; pathway; gastrointestinal tract
11.  Transduction-Specific ATLAS (TS-ATLAS) reveals a cohort of highly active L1 retrotransposons in human populations 
Human mutation  2013;34(7):10.1002/humu.22327.
Long INterspersed Element-1 (LINE-1 or L1) retrotransposons are the only autonomously active transposable elements in the human genome. The average human genome contains ∼80-100 active L1s, but only a subset of these L1s are highly active or ‘hot’. Human L1s are closely related in sequence, making it difficult to decipher progenitor/offspring relationships using traditional phylogenetic methods. However, L1 mRNAs can sometimes bypass their own polyadenylation signal and instead utilize fortuitous polyadenylation signals in 3′ flanking genomic DNA. Retrotransposition of the resultant mRNAs then results in lineage specific sequence ‘tags’ (i.e., 3′ transductions) that mark the descendants of active L1 progenitors. Here, we developed a method (Transduction-Specific Amplification Typing of L1 Active Subfamilies or TS-ATLAS) that exploits L1 3′ transductions to identify active L1 lineages in a genome-wide context. TS-ATLAS enabled the characterisation of a putative active progenitor of one L1 lineage that includes the disease causing L1 insertion L1RP, and the identification of new retrotransposition events within two other ‘hot’ L1 lineages. Intriguingly, the analysis of the newly discovered transduction lineage members suggests that L1 polyadenylation, even within a lineage, is highly stochastic. Thus, TS-ATLAS provides a new tool to explore the dynamics of L1 lineage evolution and retrotransposon biology.
doi:10.1002/humu.22327
PMCID: PMC3880804  PMID: 23553801
human; retrotransposon; transduction; polyadenylation; genome
12.  The Drosophila melanogaster PeptideAtlas facilitates the use of peptide data for improved fly proteomics and genome annotation 
BMC Bioinformatics  2009;10:59.
Background
Crucial foundations of any quantitative systems biology experiment are correct genome and proteome annotations. Protein databases compiled from high quality empirical protein identifications that are in turn based on correct gene models increase the correctness, sensitivity, and quantitative accuracy of systems biology genome-scale experiments.
Results
In this manuscript, we present the Drosophila melanogaster PeptideAtlas, a fly proteomics and genomics resource of unsurpassed depth. Based on peptide mass spectrometry data collected in our laboratory the portal allows querying fly protein data observed with respect to gene model confirmation and splice site verification as well as for the identification of proteotypic peptides suited for targeted proteomics studies. Additionally, the database provides consensus mass spectra for observed peptides along with qualitative and quantitative information about the number of observations of a particular peptide and the sample(s) in which it was observed.
Conclusion
PeptideAtlas is an open access database for the Drosophila community that has several features and applications that support (1) reduction of the complexity inherently associated with performing targeted proteomic studies, (2) designing and accelerating shotgun proteomics experiments, (3) confirming or questioning gene models, and (4) adjusting gene models such that they are in line with observed Drosophila peptides. While the database consists of proteomic data it is not required that the user is a proteomics expert.
doi:10.1186/1471-2105-10-59
PMCID: PMC2648944  PMID: 19210778
13.  KEGG Atlas mapping for global analysis of metabolic pathways 
Nucleic Acids Research  2008;36(Web Server issue):W423-W426.
KEGG Atlas is a new graphical interface to the KEGG suite of databases, especially to the systems information in the PATHWAY and BRITE databases. It currently consists of a single global map and an associated viewer for metabolism, covering about 120 KEGG metabolic pathway maps and about 10 BRITE hierarchies. The viewer allows the user to navigate and zoom the global map under the Ajax technology. The mapping of high-throughput experimental data onto the global map is the main use of KEGG Atlas. In the global metabolism map, the node (circle) is a chemical compound and the edge (line) is a set of reactions linked to a set of KEGG Orthology (KO) entries for enzyme genes. Once gene identifiers in different organisms are converted to the K number identifiers in the KO system, corresponding line segments can be highlighted in the global map, allowing the user to view genome sequence data as organism-specific pathways, gene expression data as up- or down-regulated pathways, etc. Once chemical compounds are converted to the C number identifiers in KEGG, metabolomics data can also be displayed in the global map. KEGG Atlas is available at http://www.genome.jp/kegg/atlas/.
doi:10.1093/nar/gkn282
PMCID: PMC2447737  PMID: 18477636
14.  An Atlas of the Speed of Copy Number Changes in Animal Gene Families and Its Implications 
PLoS ONE  2009;4(10):e7342.
The notion that gene duplications generating new genes and functions is commonly accepted in evolutionary biology. However, this assumption is more speculative from theory rather than well proven in genome-wide studies. Here, we generated an atlas of the rate of copy number changes (CNCs) in all the gene families of ten animal genomes. We grouped the gene families with similar CNC dynamics into rate pattern groups (RPGs) and annotated their function using a novel bottom-up approach. By comparing CNC rate patterns, we showed that most of the species-specific CNC rates groups are formed by gene duplication rather than gene loss, and most of the changes in rates of CNCs may be the result of adaptive evolution. We also found that the functions of many RPGs match their biological significance well. Our work confirmed the role of gene duplication in generating novel phenotypes, and the results can serve as a guide for researchers to connect the phenotypic features to certain gene duplications.
doi:10.1371/journal.pone.0007342
PMCID: PMC2761543  PMID: 19851465
15.  Regression Models of Atlas Appearance 
Models of object appearance based on principal components analysis provide powerful and versatile tools in computer vision and medical image analysis. A major shortcoming is that they rely entirely on the training data to extract principal modes of appearance variation and ignore underlying variables (e.g., subject age, gender). This paper introduces an appearance modeling framework based instead on generalized multi-linear regression. The training of regression appearance models is controlled by independent variables. This makes it straightforward to create model instances for specific values of these variables, which is akin to model interpolation. We demonstrate the new framework by creating an appearance model of the human brain from MR images of 36 subjects. Instances of the model created for different ages are compared with average shape atlases created from age-matched sub-populations. Relative tissue volumes vs. age in models are also compared with tissue volumes vs. subject age in the original images. In both experiments, we found excellent agreement between the regression models and the comparison data. We conclude that regression appearance models are a promising new technique for image analysis, with one potential application being the representation of a continuum of mutually consistent, age-specific atlases of the human brain.
PMCID: PMC2807889  PMID: 19694260
16.  Three-Dimensional Atlas System for Mouse and Rat Brain Imaging Data 
Tomographic neuroimaging techniques allow visualization of functionally and structurally specific signals in the mouse and rat brain. The interpretation of the image data relies on accurate determination of anatomical location, which is frequently obstructed by the lack of structural information in the data sets. Positron emission tomography (PET) generally yields images with low spatial resolution and little structural contrast, and many experimental magnetic resonance imaging (MRI) paradigms give specific signal enhancements but often limited anatomical information. Side-by-side comparison of image data with conventional atlas diagram is hampered by the 2-D format of the atlases, and by the lack of an analytical environment for accumulation of data and integrative analyses. We here present a method for reconstructing 3-D atlases from digital 2-D atlas diagrams, and exemplify 3-D atlas-based analysis of PET and MRI data. The reconstruction procedure is based on two seminal mouse and brain atlases, but is applicable to any stereotaxic atlas. Currently, 30 mouse brain structures and 60 rat brain structures have been reconstructed. To exploit the 3-D atlas models, we have developed a multi-platform atlas tool (available via The Rodent Workbench, http://rbwb.org) which allows combined visualization of experimental image data within the 3-D atlas space together with 3-D viewing and user-defined slicing of selected atlas structures. The tool presented facilitates assignment of location and comparative analysis of signal location in tomographic images with low structural contrast.
doi:10.3389/neuro.11.004.2007
PMCID: PMC2525992  PMID: 18974799
3-D reconstruction; atlas; brain; imaging; magnetic resonance imaging; positron emission tomography; stereotaxic; visualization
17.  Prioritization of Cancer Marker Candidates Based on the Immunohistochemistry Staining Images Deposited in the Human Protein Atlas 
PLoS ONE  2013;8(11):e81079.
Cancer marker discovery is an emerging topic in high-throughput quantitative proteomics. However, the omics technology usually generates a long list of marker candidates that requires a labor-intensive filtering process in order to screen for potentially useful markers. Specifically, various parameters, such as the level of overexpression of the marker in the cancer type of interest, which is related to sensitivity, and the specificity of the marker among cancer groups, are the most critical considerations. Protein expression profiling on the basis of immunohistochemistry (IHC) staining images is a technique commonly used during such filtering procedures. To systematically investigate the protein expression in different cancer versus normal tissues and cell types, the Human Protein Atlas is a most comprehensive resource because it includes millions of high-resolution IHC images with expert-curated annotations. To facilitate the filtering of potential biomarker candidates from large-scale omics datasets, in this study we have proposed a scoring approach for quantifying IHC annotation of paired cancerous/normal tissues and cancerous/normal cell types. We have comprehensively calculated the scores of all the 17219 tested antibodies deposited in the Human Protein Atlas based on their accumulated IHC images and obtained 457110 scores covering 20 different types of cancers. Statistical tests demonstrate the ability of the proposed scoring approach to prioritize cancer-specific proteins. Top 100 potential marker candidates were prioritized for the 20 cancer types with statistical significance. In addition, a model study was carried out of 1482 membrane proteins identified from a quantitative comparison of paired cancerous and adjacent normal tissues from patients with colorectal cancer (CRC). The proposed scoring approach demonstrated successful prioritization and identified four CRC markers, including two of the most widely used, namely CEACAM5 and CEACAM6. These results demonstrate the potential of this scoring approach in terms of cancer marker discovery and development. All the calculated scores are available at http://bal.ym.edu.tw/hpa/.
doi:10.1371/journal.pone.0081079
PMCID: PMC3841220  PMID: 24303032
18.  White Matter Atlas Generation using HARDI based Automated Parcellation 
Neuroimage  2011;59(4):4055-4063.
Most diffusion imaging studies have used subject registration to an atlas space for enhanced quantification of anatomy. However, standard diffusion tensor atlases lack information in regions of fiber crossing and are based on adult anatomy. The degree of error associated with applying these atlases to studies of children for example has not yet been estimated but may lead to suboptimal results. This paper describes a novel technique for generating population-specific high angular resolution diffusion imaging (HARDI)-based atlases consisting of labeled regions of homogenous white matter. Our approach uses a fiber orientation distribution (FOD) diffusion model and a data driven clustering algorithm. White matter regional labeling is achieved by our automated data driven clustering algorithm that has the potential to delineate white matter regions based on fiber complexity and orientation. The advantage of such an atlas is that it is study specific and more comprehensive in describing regions of white matter homogeneity as compared to standard anatomical atlases. We have applied this state of the art technique to a dataset consisting of adolescent and preadolescent children, creating one of the first examples of a HARDI-based atlas, thereby establishing the feasibility of the atlas creation framework. The white matter regions generated by our automated clustering algorithm have lower FOD variance than when compared to the regions created from a standard anatomical atlas.
doi:10.1016/j.neuroimage.2011.08.053
PMCID: PMC3272315  PMID: 21893205
Diffusion; Atlas Generation; HARDI Template; White Matter Parcellation
19.  SBMLsqueezer: A CellDesigner plug-in to generate kinetic rate equations for biochemical networks 
BMC Systems Biology  2008;2:39.
Background
The development of complex biochemical models has been facilitated through the standardization of machine-readable representations like SBML (Systems Biology Markup Language). This effort is accompanied by the ongoing development of the human-readable diagrammatic representation SBGN (Systems Biology Graphical Notation). The graphical SBML editor CellDesigner allows direct translation of SBGN into SBML, and vice versa. For the assignment of kinetic rate laws, however, this process is not straightforward, as it often requires manual assembly and specific knowledge of kinetic equations.
Results
SBMLsqueezer facilitates exactly this modeling step via automated equation generation, overcoming the highly error-prone and cumbersome process of manually assigning kinetic equations. For each reaction the kinetic equation is derived from the stoichiometry, the participating species (e.g., proteins, mRNA or simple molecules) as well as the regulatory relations (activation, inhibition or other modulations) of the SBGN diagram. Such information allows distinctions between, for example, translation, phosphorylation or state transitions. The types of kinetics considered are numerous, for instance generalized mass-action, Hill, convenience and several Michaelis-Menten-based kinetics, each including activation and inhibition. These kinetics allow SBMLsqueezer to cover metabolic, gene regulatory, signal transduction and mixed networks. Whenever multiple kinetics are applicable to one reaction, parameter settings allow for user-defined specifications. After invoking SBMLsqueezer, the kinetic formulas are generated and assigned to the model, which can then be simulated in CellDesigner or with external ODE solvers. Furthermore, the equations can be exported to SBML, LaTeX or plain text format.
Conclusion
SBMLsqueezer considers the annotation of all participating reactants, products and regulators when generating rate laws for reactions. Thus, for each reaction, only applicable kinetic formulas are considered. This modeling scheme creates kinetics in accordance with the diagrammatic representation. In contrast most previously published tools have relied on the stoichiometry and generic modulators of a reaction, thus ignoring and potentially conflicting with the information expressed through the process diagram. Additional material and the source code can be found at the project homepage (URL found in the Availability and requirements section).
doi:10.1186/1752-0509-2-39
PMCID: PMC2412839  PMID: 18447902
20.  Salivary Gland Gene Expression Atlas Identifies a New Regulator of Branching Morphogenesis 
Journal of Dental Research  2011;90(9):1078-1084.
During organ development, local changes in gene expression govern morphogenesis and cell fate. We have generated a microanatomical atlas of epithelial gene expression of embryonic salivary glands. The mouse submandibular salivary gland first appears as a single mass of epithelial cells surrounded by mesenchyme, and it undergoes rapid branching morphogenesis to form a complex secretory organ with acini connected to an extensive ductal system. Using laser capture microdissection, we collected samples from 14 distinct epithelial locations at embryonic days 12.5, 13.5, 14, and 15, and characterized their gene expression by microarray analysis. These microarray results were evaluated by qPCR of biological replicates and by comparisons of the gene expression dataset with published expression data. Using this gene expression atlas to search for novel regulators of branching morphogenesis, we found a substantial reduction in mRNA levels of GSK3β at the base of forming clefts. This unexpected finding was confirmed by immunostaining, and inhibition of GSK3β activity enhanced salivary gland branching. This first microanatomical expression atlas of a developing gland characterizes changes in local gene expression during salivary gland development and differentiation, which should facilitate the identification of key genes involved in tissue morphogenesis.
doi:10.1177/0022034511413131
PMCID: PMC3318080  PMID: 21709141
microarray; laser microdissection; branching morphogenesis; GSK3beta; organ morphogenesis; gene expression
21.  A tool to facilitate clinical biomarker studies - a tissue dictionary based on the Human Protein Atlas 
BMC Medicine  2012;10:103.
The complexity of tissue and the alterations that distinguish normal from cancer remain a challenge for translating results from tumor biological studies into clinical medicine. This has generated an unmet need to exploit the findings from studies based on cell lines and model organisms to develop, validate and clinically apply novel diagnostic, prognostic and treatment predictive markers. As one step to meet this challenge, the Human Protein Atlas project has been set up to produce antibodies towards human protein targets corresponding to all human protein coding genes and to map protein expression in normal human tissues, cancer and cells. Here, we present a dictionary based on microscopy images created as an amendment to the Human Protein Atlas. The aim of the dictionary is to facilitate the interpretation and use of the image-based data available in the Human Protein Atlas, but also to serve as a tool for training and understanding tissue histology, pathology and cell biology. The dictionary contains three main parts, normal tissues, cancer tissues and cells, and is based on high-resolution images at different magnifications of full tissue sections stained with H & E. The cell atlas is centered on immunofluorescence and confocal microscopy images, using different color channels to highlight the organelle structure of a cell. Here, we explain how this dictionary can be used as a tool to aid clinicians and scientists in understanding the use of tissue histology and cancer pathology in diagnostics and biomarker studies.
doi:10.1186/1741-7015-10-103
PMCID: PMC3523031  PMID: 22971420
Antibody-based proteomics; cancer biomarkers; tissue and cell dictionary; immunohistochemistry; protein expression; histology, pathology
22.  An atlas of tissue-specific conserved coexpression for functional annotation and disease gene prediction 
European Journal of Human Genetics  2011;19(11):1173-1180.
Gene coexpression relationships that are phylogenetically conserved between human and mouse have been shown to provide important clues about gene function that can be efficiently used to identify promising candidate genes for human hereditary disorders. In the past, such approaches have considered mostly generic gene expression profiles that cover multiple tissues and organs. The individual genes of multicellular organisms, however, can participate in different transcriptional programs, operating at scales as different as single-cell types, tissues, organs, body regions or the entire organism. Therefore, systematic analysis of tissue-specific coexpression could be, in principle, a very powerful strategy to dissect those functional relationships among genes that emerge only in particular tissues or organs. In this report, we show that, in fact, conserved coexpression as determined from tissue-specific and condition-specific data sets can predict many functional relationships that are not detected by analyzing heterogeneous microarray data sets. More importantly, we find that, when combined with disease networks, the simultaneous use of both generic (multi-tissue) and tissue-specific conserved coexpression allows a more efficient prediction of human disease genes than the use of generic conserved coexpression alone. Using this strategy, we were able to identify high-probability candidates for 238 orphan disease loci. We provide proof of concept that this combined use of generic and tissue-specific conserved coexpression can be very useful to prioritize the mutational candidates obtained from deep-sequencing projects, even in the case of genetic disorders as heterogeneous as XLMR.
doi:10.1038/ejhg.2011.96
PMCID: PMC3198151  PMID: 21654723
disease-gene prediction; functional annotation; transcriptome; phenome
23.  Brain Tissue Segmentation of Neonatal MR Images Using a Longitudinal Subject-specific Probabilistic Atlas 
Brain tissue segmentation of neonate MR images is a challenging task in study of early brain development, due to low signal contrast among brain tissues and high intensity variability especially in white matter. Among various brain tissue segmentation algorithms, the atlas-based segmentation techniques can potentially produce reasonable segmentation results on neonatal brain images. However, their performance on the population-based atlas is still limited due to the high variability of brain structures across different individuals. Moreover, it may be impossible to generate a reasonable probabilistic atlas for neonates without tissue segmentation samples. To overcome these limitations, we present a neonatal brain tissue segmentation method by taking advantage of the longitudinal data available in our study to establish a subject-specific probabilistic atlas. In particular, tissue segmentation of the neonatal brain is formulated as two iterative steps of bias correction and probabilistic atlas based tissue segmentation, along with the guidance of brain tissue segmentation resulted from the later time images of the same subject which serve as a subject-specific probabilistic atlas. The proposed method has been evaluated qualitatively through visual inspection and quantitatively by comparing with manual delineation results. Experimental results show that the utilization of a subject-specific probabilistic atlas can substantially improve tissue segmentation of neonatal brain images.
doi:10.1117/12.811610
PMCID: PMC2857333  PMID: 20414458
Neonate; Tissue segmentation; Probabilistic atlas; Subject-specific atlas
24.  Comprehensive connectivity of the mouse main olfactory bulb: analysis and online digital atlas 
We introduce the first open resource for mouse olfactory connectivity data produced as part of the Mouse Connectome Project (MCP) at UCLA. The MCP aims to assemble a whole-brain connectivity atlas for the C57Bl/6J mouse using a double coinjection tracing method. Each coinjection consists of one anterograde and one retrograde tracer, which affords the advantage of simultaneously identifying efferent and afferent pathways and directly identifying reciprocal connectivity of injection sites. The systematic application of double coinjections potentially reveals interaction stations between injections and allows for the study of connectivity at the network level. To facilitate use of the data, raw images are made publicly accessible through our online interactive visualization tool, the iConnectome, where users can view and annotate the high-resolution, multi-fluorescent connectivity data (www.MouseConnectome.org). Systematic double coinjections were made into different regions of the main olfactory bulb (MOB) and data from 18 MOB cases (~72 pathways; 36 efferent/36 afferent) currently are available to view in iConnectome within their corresponding atlas level and their own bright-field cytoarchitectural background. Additional MOB injections and injections of the accessory olfactory bulb (AOB), anterior olfactory nucleus (AON), and other olfactory cortical areas gradually will be made available. Analysis of connections from different regions of the MOB revealed a novel, topographically arranged MOB projection roadmap, demonstrated disparate MOB connectivity with anterior versus posterior piriform cortical area (PIR), and exposed some novel aspects of well-established cortical olfactory projections.
doi:10.3389/fnana.2012.00030
PMCID: PMC3412993  PMID: 22891053
main olfactory bulb; piriform cortical area; lateral olfactory tract; online digital atlas; connectome; neural tract tracing
25.  The Arabidopsis translatome cell-specific mRNA atlas 
Plant Signaling & Behavior  2010;5(3):320-324.
Plants consist of distinct cell types distinguished by position, morphological features and metabolic activities. We recently developed a method to extract cell-type specific mRNA populations by immunopurification of ribosome-associated mRNAs. Microarray profiles of 21 cell-specific mRNA populations from seedling roots and shoots comprise the Arabidopsis Translatome dataset. This gene expression atlas provides a new tool for the study of cell-specific processes. Here we provide an example of how genes involved in a pathway limited to one or few cell-types can be further characterized and new candidate genes can be predicted. Cells of the root endodermis produce suberin as an inner barrier between the cortex and stele, whereas the shoot epidermal cells form cutin as a barrier to the external environment. Both polymers consist of fatty acid derivates, and share biosynthetic origins. We use the Arabidopsis Translatome dataset to demonstrate the significant cell-specific expression patterns of genes involved in those biosynthetic processes and suggest new candidate genes in the biosynthesis of suberin and cutin.
PMCID: PMC2881290  PMID: 20220312
cell-type specific expression; polysome immunopurification; translatome; suberin; cutin; endodermis; epidermis; arabidopsis

Results 1-25 (908529)