Perspectives of a systems biology of the brain: the big data conundrum understanding psychiatric diseases.

Psychiatric diseases provoke human tragedies. Asocial behaviour, mood imbalance, uncontrolled affect, and cognitive malfunction are the price for the biological and social complexity of neurobiology. To understand the etiology and to influence the onset and progress of mental diseases remains of upmost importance, but despite the much improved care for the patients, more then 100 years of research have not succeeded to understand the basic disease mechanisms and enabling rationale treatment. With the advent of the genome based technologies, much hope has been created to join the various dimension of -omics data to uncover the secrets of mental illness. Big Data as generated by -omics do not come with explanations. In this essay, I will discuss the inherent, not well understood methodological foundations and problems that seriously obstacle in striving for a quick success and may render lucky strikes impossible.

Affective disorders as complex dynamic diseases--a perspective from systems biology.

Understanding mental disorders and their neurobiological basis encompasses the conceptual management of "complexity" and "dynamics". For example, affective disorders exhibit several fluctuating state variables on psychological and biological levels and data collected of these systems levels suggest quasi-chaotic periodicity leading to use concepts and tools of the mathematics of nonlinear dynamic systems. Regarding this, we demonstrate that the concept of "Dynamic Diseases" could be a fruitful way for theory and empirical research in neuropsychiatry. In a first step, as an example, we focus on the analysis of dynamic cortisol regulation that is important for understanding depressive disorders. In this case, our message is that extremely complex phenomena of a disease may be explained as resulting from perplexingly simple nonlinear interactions of a very small number of variables. Additionally, we propose that and how widely used complex circuit diagrams representing the macroanatomic structures and connectivities of the brain involved in major depression or other mental disorders may be "animated" by quantification, even by using expert-based estimations (dummy variables). This method of modeling allows to develop exploratory computer-based numerical models that encompass the option to explore the system by computer simulations (in-silico experiments). Also inter- and intracellular molecular networks involved in affective disorders could be modeled by this procedure. We want to stimulate future research in this theoretical context.

Perspectives of a systems biology of the synapse: how to transform an indefinite data space into a model?

Understanding the synapse and its role in the development of psychiatric disorders is not only a demanding but a highly relevant challenge for neuroscience. With the advancement of modern high-throughput technologies, the amount of data collected becomes incomprehensible and the volume of information intractable for the individual scientist. Why Systems Biology opens alternatives to organize information and to deduce knowledge that can be scrutinized by rationally designed experiments? We discuss some of the fundamental ideas why Systems Biology is indeed an alternative to reductionism and show an example how semantics may help to exploit the rich source of the scientific literature to generate qualitative models of functional modules.

Informatics and medicine--from molecules to populations.

OBJECTIVES: To clarify challenges and research topics for informatics in health and to describe new approaches for interdisciplinary collaboration and education. METHODS: Research challenges and possible solutions were elaborated by scientists of two universities using an interdisciplinary approach, in a series of meetings over several months. RESULTS AND CONCLUSION: In order to translate scientific results from bench to bedside and further into an evidence-based and efficient health system, intensive collaboration is needed between experts from medicine, biology, informatics, engineering, public health, as well as social and economic sciences. Research challenges can be attributed to four areas: bioinformatics and systems biology, biomedical engineering and informatics, health informatics and individual healthcare, and public health informatics. In order to bridge existing gaps between different disciplines and cultures, we suggest focusing on interdisciplinary education, taking an integrative approach and starting interdisciplinary practice at early stages of education.

MIPS: analysis and annotation of genome information in 2007.

The Munich Information Center for Protein Sequences (MIPS-GSF, Neuherberg, Germany) combines automatic processing of large amounts of sequences with manual annotation of selected model genomes. Due to the massive growth of the available data, the depth of annotation varies widely between independent databases. Also, the criteria for the transfer of information from known to orthologous sequences are diverse. To cope with the task of global in-depth genome annotation has become unfeasible. Therefore, our efforts are dedicated to three levels of annotation: (i) the curation of selected genomes, in particular from fungal and plant taxa (e.g. CYGD, MNCDB, MatDB), (ii) the comprehensive, consistent, automatic annotation employing exhaustive methods for the computation of sequence similarities and sequence-related attributes as well as the classification of individual sequences (SIMAP, PEDANT and FunCat) and (iii) the compilation of manually curated databases for protein interactions based on scrutinized information from the literature to serve as an accepted set of reliable annotated interaction data (MPACT, MPPI, CORUM). All databases and tools described as well as the detailed descriptions of our projects can be accessed through the MIPS web server (http://mips.gsf.de).

MIPS: analysis and annotation of proteins from whole genomes in 2005.

The Munich Information Center for Protein Sequences (MIPS at the GSF), Neuherberg, Germany, provides resources related to genome information. Manually curated databases for several reference organisms are maintained. Several of these databases are described elsewhere in this and other recent NAR database issues. In a complementary effort, a comprehensive set of >400 genomes automatically annotated with the PEDANT system are maintained. The main goal of our current work on creating and maintaining genome databases is to extend gene centered information to information on interactions within a generic comprehensive framework. We have concentrated our efforts along three lines (i) the development of suitable comprehensive data structures and database technology, communication and query tools to include a wide range of different types of information enabling the representation of complex information such as functional modules or networks Genome Research Environment System, (ii) the development of databases covering computable information such as the basic evolutionary relations among all genes, namely SIMAP, the sequence similarity matrix and the CABiNet network analysis framework and (iii) the compilation and manual annotation of information related to interactions such as protein-protein interactions or other types of relations (e.g. MPCDB, MPPI, CYGD). All databases described and the detailed descriptions of our projects can be accessed through the MIPS WWW server (http://mips.gsf.de).

CYGD: the Comprehensive Yeast Genome Database.

The Comprehensive Yeast Genome Database (CYGD) compiles a comprehensive data resource for information on the cellular functions of the yeast Saccharomyces cerevisiae and related species, chosen as the best understood model organism for eukaryotes. The database serves as a common resource generated by a European consortium, going beyond the provision of sequence information and functional annotations on individual genes and proteins. In addition, it provides information on the physical and functional interactions among proteins as well as other genetic elements. These cellular networks include metabolic and regulatory pathways, signal transduction and transport processes as well as co-regulated gene clusters. As more yeast genomes are published, their annotation becomes greatly facilitated using S.cerevisiae as a reference. CYGD provides a way of exploring related genomes with the aid of the S.cerevisiae genome as a backbone and SIMAP, the Similarity Matrix of Proteins. The comprehensive resource is available under http://mips.gsf.de/genre/proj/yeast/.

The Helmholtz Network for Bioinformatics: an integrative web portal for bioinformatics resources.

SUMMARY: The Helmholtz Network for Bioinformatics (HNB) is a joint venture of eleven German bioinformatics research groups that offers convenient access to numerous bioinformatics resources through a single web portal. The 'Guided Solution Finder' which is available through the HNB portal helps users to locate the appropriate resources to answer their queries by employing a detailed, tree-like questionnaire. Furthermore, automated complex tool cascades ('tasks'), involving resources located on different servers, have been implemented, allowing users to perform comprehensive data analyses without the requirement of further manual intervention for data transfer and re-formatting. Currently, automated cascades for the analysis of regulatory DNA segments as well as for the prediction of protein functional properties are provided. AVAILABILITY: The HNB portal is available at http://www.hnbioinfo.de

MIPS: analysis and annotation of proteins from whole genomes.

The Munich Information Center for Protein Sequences (MIPS-GSF), Neuherberg, Germany, provides protein sequence-related information based on whole-genome analysis. The main focus of the work is directed toward the systematic organization of sequence-related attributes as gathered by a variety of algorithms, primary information from experimental data together with information compiled from the scientific literature. MIPS maintains automatically generated and manually annotated genome-specific databases, develops systematic classification schemes for the functional annotation of protein sequences and provides tools for the comprehensive analysis of protein sequences. This report updates the information on the yeast genome (CYGD), the Neurospora crassa genome (MNCDB), the database of complete cDNAs (German Human Genome Project, NGFN), the database of mammalian protein-protein interactions (MPPI), the database of FASTA homologies (SIMAP), and the interface for the fast retrieval of protein-associated information (QUIPOS). The Arabidopsis thaliana database, the rice database, the plant EST databases (MATDB, MOsDB, SPUTNIK), as well as the databases for the comprehensive set of genomes (PEDANT genomes) are described elsewhere in the 2003 and 2004 NAR database issues, respectively. All databases described, and the detailed descriptions of our projects can be accessed through the MIPS web server (http://mips.gsf.de).

Functional modules by relating protein interaction networks and gene expression.

Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships.

MIPS: a database for genomes and protein sequences.

The Munich Information Center for Protein Sequences (MIPS-GSF, Neuherberg, Germany) continues to provide genome-related information in a systematic way. MIPS supports both national and European sequencing and functional analysis projects, develops and maintains automatically generated and manually annotated genome-specific databases, develops systematic classification schemes for the functional annotation of protein sequences, and provides tools for the comprehensive analysis of protein sequences. This report updates the information on the yeast genome (CYGD), the Neurospora crassa genome (MNCDB), the databases for the comprehensive set of genomes (PEDANT genomes), the database of annotated human EST clusters (HIB), the database of complete cDNAs from the DHGP (German Human Genome Project), as well as the project specific databases for the GABI (Genome Analysis in Plants) and HNB (Helmholtz-Netzwerk Bioinformatik) networks. The Arabidospsis thaliana database (MATDB), the database of mitochondrial proteins (MITOP) and our contribution to the PIR International Protein Sequence Database have been described elsewhere [Schoof et al. (2002) Nucleic Acids Res., 30, 91-93; Scharfe et al. (2000) Nucleic Acids Res., 28, 155-158; Barker et al. (2001) Nucleic Acids Res., 29, 29-32]. All databases described, the protein analysis tools provided and the detailed descriptions of our projects can be accessed through the MIPS World Wide Web server (http://mips.gsf.de).

MIPS Arabidopsis thaliana Database (MAtDB): an integrated biological knowledge resource based on the first complete plant genome.

Arabidopsis thaliana is the first plant for which the complete genome has been sequenced and published. Annotation of complex eukaryotic genomes requires more than the assignment of genetic elements to the sequence. Besides completing the list of genes, we need to discover their cellular roles, their regulation and their interactions in order to understand the workings of the whole plant. The MIPS Arabidopsis thaliana Database (MAtDB; http://mips.gsf.de/proj/thal/db) started out as a repository for genome sequence data in the European Scientists Sequencing Arabidopsis (ESSA) project and the Arabidopsis Genome Initiative. Our aim is to transform MAtDB into an integrated biological knowledge resource by integrating diverse data, tools, query and visualization capabilities and by creating a comprehensive resource for Arabidopsis as a reference model for other species, including crop plants.

SNAPping up functionally related genes based on context information: a colinearity-free approach.

We describe a computational approach for finding genes that are functionally related but do not possess any noticeable sequence similarity. Our method, which we call SNAP (similarity-neighborhood approach), reveals the conservation of gene order on bacterial chromosomes based on both cross-genome comparison and context information. The novel feature of this method is that it does not rely on detection of conserved colinear gene strings. Instead, we introduce the notion of a similarity-neighborhood graph (SN-graph), which is constructed from the chains of similarity and neighborhood relationships between orthologous genes in different genomes and adjacent genes in the same genome, respectively. An SN-cycle is defined as a closed path on the SN-graph and is postulated to preferentially join functionally related gene products that participate in the same biochemical or regulatory process. We demonstrate the substantial non-randomness and functional significance of SN-cycles derived from real genome data and estimate the prediction accuracy of SNAP in assigning broad function to uncharacterized proteins. Examples of practical application of SNAP for improving the quality of genome annotation are described.

Conservation of microstructure between a sequenced region of the genome of rice and multiple segments of the genome of Arabidopsis thaliana.

The nucleotide sequence was determined for a 340-kb segment of rice chromosome 2, revealing 56 putative protein-coding genes. This represents a density of one gene per 6.1 kb, which is higher than was reported for a previously sequenced segment of the rice genome. Sixteen of the putative genes were supported by matches to ESTs. The predicted products of 29 of the putative genes showed similarity to known proteins, and a further 17 genes showed similarity only to predicted or hypothetical proteins identified in genome sequence data. The region contains a few transposable elements: one retrotransposon, and one transposon. The segment of the rice genome studied had previously been identified as representing a part of rice chromosome 2 that may be homologous to a segment of Arabidopsis chromosome 4. We confirmed the conservation of gene content and order between the two genome segments. In addition, we identified a further four segments of the Arabidopsis genome that contain conserved gene content and order. In total, 22 of the 56 genes identified in the rice genome segment were represented in this set of Arabidopsis genome segments, with at least five genes present, in conserved order, in each segment. These data are consistent with the hypothesis that the Arabidopsis genome has undergone multiple duplication events. Our results demonstrate that conservation of the genome microstructure can be identified even between monocot and dicot species. However, the frequent occurrence of duplication, and subsequent microstructure divergence, within plant genomes may necessitate the integration of subsets of genes present in multiple redundant segments to deduce evolutionary relationships and identify orthologous genes.

The HIB database of annotated UniGene clusters.

SUMMARY: The HumanInfoBase (HIB) is a database of putative human gene transcripts. UniGene clusters are assembled, and the resulting consensus sequences are submitted to the PEDANT software system (Frishman,D., Albermann,K., Hani,J., Heumann,K., Metanomski,A., Zollner,A. and Mewes,H.-W., 2001, Bioinformatics, 17, 44--57) for fully automatic sequence analysis and annotation. Predicted transcripts are classified using a variety of functional and structural categories, and hyperlinks to various databases are provided for additional information. A WWW-based graphical user interface represents the assembly process as well as functionally important sites in the putative transcripts.

Sequence and analysis of the Arabidopsis genome.

The comprehensive analysis of the genome sequence of the plant Arabidopsis thaliana has been completed recently. The genome sequence and associated analyses provide the foundations for rapid progress in many fields of plant research, such as the exploitation of genetic variation in Arabidopsis ecotypes, the assessment of the transcriptome and proteome, and the association of genome changes at the sequence level with evolutionary processes. Nevertheless, genome sequencing and analysis are only the first steps towards a new plant biology. Much remains to be done to refine the analysis of encoded genes, to define the functions of encoded proteins systematically, and to establish new generations of databases to capture and relate diverse data sets generated in widely distributed laboratories.

Toward a catalog of human genes and proteins: sequencing and analysis of 500 novel complete protein coding human cDNAs.

With the complete human genomic sequence being unraveled, the focus will shift to gene identification and to the functional analysis of gene products. The generation of a set of cDNAs, both sequences and physical clones, which contains the complete and noninterrupted protein coding regions of all human genes will provide the indispensable tools for the systematic and comprehensive analysis of protein function to eventually understand the molecular basis of man. Here we report the sequencing and analysis of 500 novel human cDNAs containing the complete protein coding frame. Assignment to functional categories was possible for 52% (259) of the encoded proteins, the remaining fraction having no similarities with known proteins. By aligning the cDNA sequences with the sequences of the finished chromosomes 21 and 22 we identified a number of genes that either had been completely missed in the analysis of the genomic sequences or had been wrongly predicted. Three of these genes appear to be present in several copies. We conclude that full-length cDNA sequencing continues to be crucial also for the accurate identification of genes. The set of 500 novel cDNAs, and another 1000 full-coding cDNAs of known transcripts we have identified, adds up to cDNA representations covering 2%--5 % of all human genes. We thus substantially contribute to the generation of a gene catalog, consisting of both full-coding cDNA sequences and clones, which should be made freely available and will become an invaluable tool for detailed functional studies.