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- Alexandersson, Marina, 1972, et al.
(author)
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Genome sequence of the Brown Norway rat yields insights into mammalian evolution
- 2004
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In: Nature. - 0028-0836 .- 1476-4687. ; 428:6982, s. 493-521
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Journal article (peer-reviewed)abstract
- The laboratory rat (Rattus norvegicus) is an indispensable tool in experimental medicine and drug development, having made inestimable contributions to human health. We report here the genome sequence of the Brown Norway (BN) rat strain. The sequence represents a high-quality ‘draft’ covering over 90% of the genome. The BN rat sequence is the third complete mammalian genome to be deciphered, and three-way comparisons with the human and mouse genomes resolve details of mammalian evolution. This first comprehensive analysis includes genes and proteins and their relation to human disease, repeated sequences, comparative genome-wide studies of mammalian orthologous chromosomal regions and rearrangement breakpoints, reconstruction of ancestral karyotypes and the events leading to existing species, rates of variation, and lineage-specific and lineageindependent evolutionary events such as expansion of gene families, orthology relations and protein evolution.
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- Eriksson, Anders, 1975, et al.
(author)
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Gene-history correlation and population structure.
- 2004
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In: Physical biology. - : IOP Publishing. - 1478-3967 .- 1478-3975. ; 1:3-4, s. 220-8
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Journal article (peer-reviewed)abstract
- Correlation of gene histories in the human genome determines the patterns of genetic variation (haplotype structure) and is crucial to understanding genetic factors in common diseases. We derive closed analytical expressions for the correlation of gene histories in established demographic models for genetic evolution and show how to extend the analysis to more realistic (but more complicated) models of demographic structure. We identify two contributions to the correlation of gene histories in divergent populations: linkage disequilibrium, and differences in the demographic history of individuals in the sample. These two factors contribute to correlations at different length scales: the former at small, and the latter at large scales. We show that recent mixing events in divergent populations limit the range of correlations and compare our findings to empirical results on the correlation of gene histories in the human genome.
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- Dewey, C., et al.
(author)
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Accurate Identification of Novel Human Genes Through Simultaneous Gene Prediction in Human, Mouse and Rat
- 2004
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In: Genome Research. - 1088-9051 .- 1549-5469. ; 14:4, s. 661-664
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Journal article (peer-reviewed)abstract
- We describe a new method for simultaneously identifying novel homologous genes with identical structure in the human, mouse, and rat genomes by combining pairwise predictions made with the SLAM gene-finding program. Using this method, we found 3698 gene triples in the human, mouse, and rat genomes which are predicted with exactly the same gene structure. We show, both computationally and experimentally, that the introns of these triples are predicted accurately as compared with the introns of other ab initio gene prediction sets. Computationally, we compared the introns of these gene triples, as well as those from other ab initio gene finders, with known intron annotations. We show that a unique property of SLAM, namely that it predicts gene structures simultaneously in two organisms, is key to producing sets of predictions that are highly accurate in intron structure when combined with other programs. Experimentally, we performed reverse transcription-polymerase chain reaction (RT-PCR) in both the human and rat to test the exon pairs flanking introns from a subset of the gene triples for which the human gene had not been previously identified. By performing RT-PCR on orthologous introns in both the human and rat genomes, we additionally explore the validity of using RT-PCR as a method for confirming gene predictions.
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- Nilsson, R. Henrik, 1976, et al.
(author)
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Towards an automated phylogenetic classification of homobasidiomycetes
- 2004
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In: Mycological Society of America (MSA) Meeting 2004.
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Conference paper (other academic/artistic)abstract
- The prospects of a phylogeny-driven classification of the higher fungi are discussed, and a new software package - mor - that seeks to facilitate such classifications is presented.
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- Verikas, Antanas, 1951-, et al.
(author)
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Selecting neural networks for making a committee decision
- 2002
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In: ARTIFICIAL NEURAL NETWORKS - ICANN 2002. - Berlin : Springer Berlin/Heidelberg. - 9783540440741 - 9783540460848 ; , s. 420-425
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Conference paper (peer-reviewed)abstract
- To improve recognition results, decisions of multiple neural networks can be aggregated into a committee decision. In contrast to the ordinary approach of utilizing all neural networks available to make a committee decision, we propose creating adaptive committees, which are specific for each input data point. A prediction network is used to identify classification neural networks to be fused for making a committee decision about a given input data point. The jth output value of the prediction network expresses the expectation level that the jth classification neural network will make a correct decision about the class label of a given input data point. The effectiveness of the approach is demonstrated on two artificial and three real data sets.
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- Verikas, Antanas, 1951-, et al.
(author)
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Selecting salient features for classification committees
- 2003
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In: Artificial Neural Networks and Neural Information Processing — ICANN/ICONIP 2003. - Heidelberg : Springer Berlin/Heidelberg. - 9783540404088 - 9783540449898 ; , s. 35-42
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Conference paper (peer-reviewed)abstract
- We present a neural network based approach for identifying salient features for classification in neural network committees. Our approach involves neural network training with an augmented cross-entropy error function. The augmented error function forces the neural network to keep low derivatives of the transfer functions of neurons of the network when learning a classification task. Feature selection is based on two criteria, namely the reaction of the cross-validation data set classification error due to the removal of the individual features and the diversity of neural networks comprising the committee. The algorithm developed removed a large number of features from the original data sets without reducing the classification accuracy of the committees. By contrast, the accuracy of the committees utilizing the reduced feature sets was higher than those exploiting all the original features. © Springer-Verlag Berlin Heidelberg 2003.
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- Gabrielsson, Britt, 1957, et al.
(author)
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Partial genome scale analysis of gene expression in human adipose tissue using DNA array
- 2000
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In: Obesity Research. - 1071-7323 .- 1550-8528. ; 8:5, s. 374-84
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Journal article (peer-reviewed)abstract
- OBJECTIVE: Large scale analysis of gene expression in adipose tissue provides a basis for the identification of novel candidate genes involved in the pathophysiology of obesity. Our goal was to explore gene expression in human adipose tissue at a partial genome scale using DNA array. RESEARCH METHODS AND PROCEDURES: Labeled cDNA, derived from human adipose tissue poly(A+) RNA, was hybridized to a DNA array containing over 18,000 human expressed sequence-tagged (EST) clones. The results were analyzed by database searches. RESULTS: Homology searches of the 300 EST clones with highest hybridization signals revealed that 145 contained DNA sequences identical to known genes and 79 could be linked to UniGene clusters. Of the 145 identified genes, 136 were nonredundant and subsequently characterized with respect to function and chromosomal localization by searching MEDLINE, UniGene, GeneMap, OMIM, SWISS-PROT, the Genome Database, and the Location Data Base. The identified genes were grouped according to their putative functions; cell/organism defense (9.6%), cell division (5.1%), cell signaling/communication (19.8%), cell structure/motility (12.5%), gene/ protein expression (16.9%), metabolism (16.2%), and unclassified (19.8%). Less than 50% of these genes have previously been reported to be expressed in adipose tissue. The chromosomal localization of 268 genes strongly expressed in adipose tissue showed that their relative abundance was significantly increased on chromosomes 11, 19, and 22 compared to the expected distribution of the same number of random genes. DISCUSSION: Our study resulted in the identification of numerous genes previously not reported to be expressed in adipose tissue. These results suggest that DNA array is a powerful tool in the search for novel regulatory pathways within adipose tissue on a scale that is not possible using conventional methods.
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Artificial Neural Networks in Medicine and Biology
- 2000
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Editorial collection (other academic/artistic)abstract
- This book contains the proceedings of ANNIMAB-1, the first international conference on artificial neural networks in medicine and biology. Comprising a selection of papers from leading researchers in the field, it summarises the state-of-the-art, analyses the relationship between ANN techniques and other available methods and points to possible future biomedical and medical uses of ANNs.
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