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Biomedical subjects

Christos A Ouzounis

Publications and source records attributed to Christos A Ouzounis.

At least 19 recordsLinked to original sources
PubMed2006

Structural and functional properties of genes involved in human cancer.

BACKGROUND: One of the main goals of cancer genetics is to identify the causative elements at the molecular level leading to cancer. RESULTS: We have conducted an analysis of a set of genes known to be involved in cancer in order to unveil their unique features that can assist towards the identification of new candidate cancer genes. CONCLUSION: We have detected key patterns in this group of genes in terms of the molecular function or the biological process in which they are involved as well as sequence properties. Based on these features we have developed an accurate Bayesian classification model with which human genes have been scored for their likelihood of involvement in cancer.

Amino Acid Sequence↗
PubMed2005

A minimal estimate for the gene content of the last universal common ancestor--exobiology from a terrestrial perspective.

Using an algorithm for ancestral state inference of gene content, given a large number of extant genome sequences and a phylogenetic tree, we aim to reconstruct the gene content of the last universal common ancestor (LUCA), a hypothetical life form that presumably was the progenitor of the three domains of life. The method allows for gene loss, previously found to be a major factor in shaping gene content, and thus the estimate of LUCA's gene content appears to be substantially higher than that proposed previously, with a typical number of over 1000 gene families, of which more than 90% are also functionally characterized. More precisely, when only prokaryotes are considered, the number varies between 1006 and 1189 gene families while when eukaryotes are also included, this number increases to between 1344 and 1529 families depending on the underlying phylogenetic tree. Therefore, the common belief that the hypothetical genome of LUCA should resemble those of the smallest extant genomes of obligate parasites is not supported by recent advances in computational genomics. Instead, a fairly complex genome similar to those of free-living prokaryotes, with a variety of functional capabilities including metabolic transformation, information processing, membrane/transport proteins and complex regulation, shared between the three domains of life, emerges as the most likely progenitor of life on Earth, with profound repercussions for planetary exploration and exobiology.

Algorithms↗
PubMed2005

Probabilistic annotation of protein sequences based on functional classifications.

BACKGROUND: One of the most evident achievements of bioinformatics is the development of methods that transfer biological knowledge from characterised proteins to uncharacterised sequences. This mode of protein function assignment is mostly based on the detection of sequence similarity and the premise that functional properties are conserved during evolution. Most automatic approaches developed to date rely on the identification of clusters of homologous proteins and the mapping of new proteins onto these clusters, which are expected to share functional characteristics. RESULTS: Here, we inverse the logic of this process, by considering the mapping of sequences directly to a functional classification instead of mapping functions to a sequence clustering. In this mode, the starting point is a database of labelled proteins according to a functional classification scheme, and the subsequent use of sequence similarity allows defining the membership of new proteins to these functional classes. In this framework, we define the Correspondence Indicators as measures of relationship between sequence and function and further formulate two Bayesian approaches to estimate the probability for a sequence of unknown function to belong to a functional class. This approach allows the parametrisation of different sequence search strategies and provides a direct measure of annotation error rates. We validate this approach with a database of enzymes labelled by their corresponding four-digit EC numbers and analyse specific cases. CONCLUSION: The performance of this method is significantly higher than the simple strategy consisting in transferring the annotation from the highest scoring BLAST match and is expected to find applications in automated functional annotation pipelines.

Algorithms↗
PubMed2005

Sensitive detection of sequence similarity using combinatorial pattern discovery: a challenging study of two distantly related protein families.

We investigate the performance of combinatorial pattern discovery to detect remote sequence similarities in terms of both biological accuracy and computational efficiency for a pair of distantly related families, as a case study. The two families represent the cupredoxins and multicopper oxidases, both containing blue copper-binding domains. These families present a challenging case due to low sequence similarity, different local structure, and variable sequence conservation at their copper-binding active sites. In this study, we investigate a new approach for automatically identifying weak sequence similarities that is based on combinatorial pattern discovery. We compare its performance with a traditional, HMM-based scheme and obtain estimates for sensitivity and specificity of the two approaches. Our analysis suggests that pattern discovery methods can be substantially more sensitive in detecting remote protein relationships while at the same time guaranteeing high specificity.

Amino Acid Sequence↗
PubMed2005

Highly consistent patterns for inherited human diseases at the molecular level.

Over 1600 mammalian genes are known to cause an inherited disorder, when subjected to one or more mutations. These disease genes represent a unique resource for the identification and quantification of relationships between phenotypic attributes of a disease and the molecular features of the associated disease genes, including their ascribed annotated functional classes and expression patterns. Such analyses can provide a more global perspective and a deeper understanding of the probable causes underlying human hereditary diseases. In this perspective and critical view of disease genomics, we present a comparative analysis of genes reported to cause inherited diseases in humans in terms of their causative effects on physiology, their genetics and inheritance modes, the functional processes they are involved in and their expression profiles across a wide spectrum of tissues. Our analysis reveals that there are more extensive correlations between these attributes of genetic disease genes than previously appreciated. For instance, the functional pattern of genes causing dominant and recessive diseases is markedly different. Also, the function of the genes and their expression correlate with the type of disease they cause when mutated. The results further indicate that a comparative genomics approach for the analysis of genes linked to human genetic diseases will facilitate the elucidation of the underlying molecular and cellular mechanisms.

Biomarkers↗
PubMed2005

Expansion of the BioCyc collection of pathway/genome databases to 160 genomes.

The BioCyc database collection is a set of 160 pathway/genome databases (PGDBs) for most eukaryotic and prokaryotic species whose genomes have been completely sequenced to date. Each PGDB in the BioCyc collection describes the genome and predicted metabolic network of a single organism, inferred from the MetaCyc database, which is a reference source on metabolic pathways from multiple organisms. In addition, each bacterial PGDB includes predicted operons for the corresponding species. The BioCyc collection provides a unique resource for computational systems biology, namely global and comparative analyses of genomes and metabolic networks, and a supplement to the BioCyc resource of curated PGDBs. The Omics viewer available through the BioCyc website allows scientists to visualize combinations of gene expression, proteomics and metabolomics data on the metabolic maps of these organisms. This paper discusses the computational methodology by which the BioCyc collection has been expanded, and presents an aggregate analysis of the collection that includes the range of number of pathways present in these organisms, and the most frequently observed pathways. We seek scientists to adopt and curate individual PGDBs within the BioCyc collection. Only by harnessing the expertise of many scientists we can hope to produce biological databases, which accurately reflect the depth and breadth of knowledge that the biomedical research community is producing.

Animals↗
PubMed2005

Ancestral state reconstructions for genomes.

The recent expansion of phylogenetic analysis from the traditional field of molecular evolution, analyzing histories of genes, to the nascent field of "genomic evolution", analyzing histories of entire genomes, enables the construction of trees based on genome information, the quantification of the key processes that shape genome content and, ultimately, plausible parsimony reconstructions of ancestral genomes. Thus, when genomes are considered as phylogenetic characters, it is possible to reconstruct not only the history of species but also the ancestral states in terms of genome structure or function. In the future, we might be able to accurately reconstruct--or retrodict--a chain of events that led to the emergence of a specific genome sequence and, ultimately, to synthesize ancestral genomes at will, creating a "Jurassic database" of genomes.

Evolution, Molecular↗
PubMed2005

CoGenT++: an extensive and extensible data environment for computational genomics.

MOTIVATION: CoGenT++ is a data environment for computational research in comparative and functional genomics, designed to address issues of consistency, reproducibility, scalability and accessibility. DESCRIPTION: CoGenT++ facilitates the re-distribution of all fully sequenced and published genomes, storing information about species, gene names and protein sequences. We describe our scalable implementation of ProXSim, a continually updated all-against-all similarity database, which stores pairwise relationships between all genome sequences. Based on these similarities, derived databases are generated for gene fusions--AllFuse, putative orthologs--OFAM, protein families--TRIBES, phylogenetic profiles--ProfUse and phylogenetic trees. Extensions based on the CoGenT++ environment include disease gene prediction, pattern discovery, automated domain detection, genome annotation and ancestral reconstruction. CONCLUSION: CoGenT++ provides a comprehensive environment for computational genomics, accessible primarily for large-scale analyses as well as manual browsing.

Chromosome Mapping↗
PubMed2005

The net of life: reconstructing the microbial phylogenetic network.

It has previously been suggested that the phylogeny of microbial species might be better described as a network containing vertical and horizontal gene transfer (HGT) events. Yet, all phylogenetic reconstructions so far have presented microbial trees rather than networks. Here, we present a first attempt to reconstruct such an evolutionary network, which we term the "net of life". We use available tree reconstruction methods to infer vertical inheritance, and use an ancestral state inference algorithm to map HGT events on the tree. We also describe a weighting scheme used to estimate the number of genes exchanged between pairs of organisms. We demonstrate that vertical inheritance constitutes the bulk of gene transfer on the tree of life. We term the bulk of horizontal gene flow between tree nodes as "vines", and demonstrate that multiple but mostly tiny vines interconnect the tree. Our results strongly suggest that the HGT network is a scale-free graph, a finding with important implications for genome evolution. We propose that genes might propagate extremely rapidly across microbial species through the HGT network, using certain organisms as hubs.

Algorithms↗
PubMed2005

MagicMatch--cross-referencing sequence identifiers across databases.

MOTIVATION: At present, mapping of sequence identifiers across databases is a daunting, time-consuming and computationally expensive process, usually achieved by sequence similarity searches with strict threshold values. SUMMARY: We present a rapid and efficient method to map sequence identifiers across databases. The method uses the MD5 checksum algorithm for message integrity to generate sequence fingerprints and uses these fingerprints as hash strings to map sequences across databases. The program, called MagicMatch, is able to cross-link any of the major sequence databases within a few seconds on a modest desktop computer.

Algorithms↗
PubMed2005

The properties of protein family space depend on experimental design.

MOTIVATION: Databases of protein families often exhibit drastically different properties of the protein family space. RESULTS: We compared the properties of protein family space as reflected by exhaustive protein family databases and databases with predefined families. We used TRIBES, Protomap, ProDom and COGs as representatives of the exhaustive databases, and Pfam-A and Superfamily as databases that predefine families. We observe a power-law distribution of family sizes in all these databases, albeit in predefined databases the power-law line collapses before reaching smaller sized families. We discuss the future trends of this power-law distribution and suggest that saturation in the sampling of protein family space will result in a distortion of the power law in small family sizes. For larger genome sizes, predefined databases show logarithmic growth of the number of families per genome, whereas exhaustive databases exhibit a virtually linear relationship. All databases consistently differ in the proportion of protein families shared between taxa. Predefined databases have a larger number of protein families shared between the three domains of life, while exhaustive databases show a much more fragmented distribution. We argue that these discrepancies reflect alternative approaches to the trade-off issue of sensitivity versus specificity in the detection of homologous proteins. We conclude that these properties are complementary rather than contradictory, while describing the protein universe from different perspectives.

Algorithms↗
PubMed2005

Clustering the annotation space of proteins.

BACKGROUND: Current protein clustering methods rely on either sequence or functional similarities between proteins, thereby limiting inferences to one of these areas. RESULTS: Here we report a new approach, named CLAN, which clusters proteins according to both annotation and sequence similarity. This approach is extremely fast, clustering the complete SwissProt database within minutes. It is also accurate, recovering consistent protein families agreeing on average in more than 97% with sequence-based protein families from Pfam. Discrepancies between sequence- and annotation-based clusters were scrutinized and the reasons reported. We demonstrate examples for each of these cases, and thoroughly discuss an example of a propagated error in SwissProt: a vacuolar ATPase subunit M9.2 erroneously annotated as vacuolar ATP synthase subunit H. CLAN algorithm is available from the authors and the CLAN database is accessible at http://maine.ebi.ac.uk:8000/cgi-bin/clan/ClanSearch.pl CONCLUSIONS: CLAN creates refined function-and-sequence specific protein families that can be used for identification and annotation of unknown family members. It also allows easy identification of erroneous annotations by spotting inconsistencies between similarities on annotation and sequence levels.

Adenosine Triphosphatases↗
PubMed2005

Measuring genome conservation across taxa: divided strains and united kingdoms.

Species evolutionary relationships have traditionally been defined by sequence similarities of phylogenetic marker molecules, recently followed by whole-genome phylogenies based on gene order, average ortholog similarity or gene content. Here, we introduce genome conservation--a novel metric of evolutionary distances between species that simultaneously takes into account, both gene content and sequence similarity at the whole-genome level. Genome conservation represents a robust distance measure, as demonstrated by accurate phylogenetic reconstructions. The genome conservation matrix for all presently sequenced organisms exhibits a remarkable ability to define evolutionary relationships across all taxonomic ranges. An assessment of taxonomic ranks with genome conservation shows that certain ranks are inadequately described and raises the possibility for a more precise and quantitative taxonomy in the future. All phylogenetic reconstructions are available at the genome phylogeny server: .

Bacteria↗
PubMed2005

Percolation of annotation errors through hierarchically structured protein sequence databases.

Databases of protein sequences have grown rapidly in recent years as a result of genome sequencing projects. Annotating protein sequences with descriptions of their biological function ideally requires careful experimentation, but this work lags far behind. Instead, biological function is often imputed by copying annotations from similar protein sequences. This gives rise to annotation errors, and more seriously, to chains of misannotation. [Percolation of annotation errors in a database of protein sequences (2002)] developed a probabilistic framework for exploring the consequences of this percolation of errors through protein databases, and applied their theory to a simple database model. Here we apply the theory to hierarchically structured protein sequence databases, and draw conclusions about database quality at different levels of the hierarchy.

Amino Acid Sequence↗
PubMed2005

BioLayout(Java): versatile network visualisation of structural and functional relationships.

Visualisation of biological networks is becoming a common task for the analysis of high-throughput data. These networks correspond to a wide variety of biological relationships, such as sequence similarity, metabolic pathways, gene regulatory cascades and protein interactions. We present a general approach for the representation and analysis of networks of variable type, size and complexity. The application is based on the original BioLayout program (C-language implementation of the Fruchterman-Rheingold layout algorithm), entirely re-written in Java to guarantee portability across platforms. BioLayout(Java) provides broader functionality, various analysis techniques, extensions for better visualisation and a new user interface. Examples of analysis of biological networks using BioLayout(Java) are presented.

Computer Graphics↗
PubMed2004

An exponential core in the heart of the yeast protein interaction network.

Protein interactions in the budding yeast have been shown to form a scale-free network, a feature of other organized networks such as bacterial and archaeal metabolism and the World Wide Web. Here, we study the connections established by yeast proteins and discover a preferential attachment between essential proteins. The essential-essential connections are long ranged and form a subnetwork where the giant component includes 97% of these proteins. Unexpectedly, this subnetwork displays an exponential connectivity distribution, in sharp contrast to the scale-free topology of the complete network. Furthermore, the wide phylogenetic extent of these core proteins and interactions provides evidence that they represent the ancestral state of the yeast protein interaction network. Finally, we propose that this core exponential network may represent a generic scaffold around which organism-specific and taxon-specific proteins and interactions coalesce.

Models, Biological↗
PubMed2004

Comparative genomics of transcriptional control in the human malaria parasite Plasmodium falciparum.

The life cycle of the parasite Plasmodium falciparum, responsible for the most deadly form of human malaria, requires specialized protein expression for survival in the mammalian host and insect vector. To identify components of processes controlling gene expression during its life cycle, the malarial genome--along with seven crown eukaryote group genomes--was queried with a reference set of transcription-associated proteins (TAPs). Following clustering on the basis of sequence similarity of the TAPs with their homologs, and together with hidden Markov model profile searches, 156 P. falciparum TAPs were identified. This represents about a third of the number of TAPs usually found in the genome of a free-living eukaryote. Furthermore, the P. falciparum genome appears to contain a low number of sequences, which are highly conserved and abundant within the kingdoms of free-living eukaryotes, that contribute to gene-specific transcriptional regulation. However, in comparison with these other eukaryotic genomes, the CCCH-type zinc finger (common in proteins modulating mRNA decay and translation rates) was found to be the most abundant in the P. falciparum genome. This observation, together with the paucity of malarial transcriptional regulators identified, suggests Plasmodium protein levels are primarily determined by posttranscriptional mechanisms.

Animals↗