It is optimal to be optimistic about survival

We investigate the optimal behaviour of an organism that is unable to obtain a reliable estimate of its mortality risk. In this case, natural selection will shape behaviour to be approximately optimal given the probability distribution of mortality risks in possible environments that the organism and its ancestors encountered. The mean of this distribution is the average mortality risk experienced by a randomly selected member of the species. We show that if an organism does not know the exact mortality risk, it should act as if the risk is less than the mean risk. This can be viewed as being optimistic. We argue that this effect is likely to be general.     

Contemporary approaches to protein structure classification

In a similar manner to sequence database searching, it is also possible to compare three-dimensional protein structures. Such methods can be extremely useful because a structural similarity may represent a distant evolutionary relationship that is undetectable by sequence analysis. In this review, we summarise the most popular structure comparison methods, show how they can be used for database searching, and then describe some of the most advanced attempts to develop comprehensive protein structure classifications. With such data, it is possible to identify distant evolutionary relationships, provide libraries of unique folds for structure prediction, estimate the total number of folds that exist, and investigate the preference for certain types of structures over others. BioEssays 20:884–891, 1998. © 1998 John Wiley & Sons, Inc.     

On What It is to Fly Can Tell Us Something About What It is to Live

The plurality of definitions of life is often perceived as an unsatisfying situation stemming from still incomplete knowledge about ‘what it is to live’ as well as from the existence of a variety of methods for reaching a definition. For many, such plurality is to be remedied and the search for a unique and fully satisfactory definition of life pursued. In this contribution on the contrary, it is argued that the existence of such a variety of definitions of life undermines the very feasibility of ever reaching a unique unambiguous definition. It is argued that focusing on the definitions of specific types of ‘living systems’—somehow in the same way that one can define specific types of ‘flying systems’—could be more fruitful from a heuristic point of view than looking for ‘the’ right definition of life, and probably more accurate in terms of carving Nature at its joints.     

Metabolomic approaches to the normal aging process

Aging is a multifaceted process involving the accumulation of diverse deleterious changes in biological systems over time, so significant alterations in cellular metabolism are detected throughout aging. In the present study, the metabolic processes relevant to the normal aging process were investigated via non-targeted metabolomics using liquid chromatography–mass spectrometry. To exclude physiological and environmental differences, the metabolic profiles and the relevant metabolic pathways were analyzed in plasma from two separate study groups comprising two distinctly aged cohorts of healthy individuals, the elderly and the younger. The first group was recruited from an urban hospital, and the second group was recruited from a rural community. Alterations in fatty acid beta-oxidation, glycerophospholipid metabolism, and sphingolipid metabolism were identified as significant metabolic pathways relevant to normal aging. It was also found that sphingosine in sphingolipid metabolism, long-chain acylcarnitines in beta-oxidation, and lysophosphatidylcholines (LysoPCs) in glycerophospholipid metabolism could be critical candidate metabolites in the aging process. These results suggest that the metabolic profile of the healthiest individuals could be associated with the normal function of mitochondria, the primary organelle of redox homeostasis, as indicated by their low acylcarnitine to l-carnitine ratio and low levels of LysoPCs and sphingosine in plasma. The present study provides a critical contribution to the entire picture of the aging process.     

Numerical approaches to lake classification with special reference to macrophyte communities

Summary Various approaches to the classification of S. Swedish lakes on the basis of their macrophyte composition are discussed. A main division is made between species or life-form, and synusia or community approaches. Three steps in the classification are discussed: primary clustering of sites to arrive at a local classification, secondary classification of clusters of sites to arrive at general community types and classification of lakes according to their community composition.The estimation of species performance is discussed and a logarithmic transformation advocated. The analysis of belt transects is suggested as a satisfactory general approach.Some problems regarding synusial independence and possible synusial interactions are mentioned. A survey of boundary types in lakes is given.Examples are given of classifications based on single life-forms and life-form combinations. Helophyte community composition of lakes is effectively shown by a combination of classification and ordination. The idea of aquatic community complexes is discussed with reference to the recent sigma-syntaxon approach in phytosociology.Nomenclature follows Lid (1974).     

It pays to be sweet: sugars in mutualistic interactions

It is common knowledge that many flowering plants produce nectar to reward pollinators. Not so well known is the fact that plants, fungi and insects also employ sugar-rich solutions to obtain transport or defensive services. However, not all of these interactions are honest. In many cases, cheaters use tricks instead of treats.     

It is alive

We need to familiarize ourselves with the facts of evolution, so that we can mount a spirited defense against creationism and the forces of ignorance.     

Synthetic approaches towards structurally diverse gamma-butyrolactone natural-product-like compounds

Natural products containing a gamma-butyrolactone ring are abundant in nature; however, few general synthetic approaches to their stereoselective synthesis with broad structural variety are known. In this article, recent developments towards mono- and polycyclic gamma-butyrolactone natural products and analogs are discussed. A special focus is given to asymmetric methods applying transition metal or organocatalysts that allow not only the efficient introduction of a broad variety of functional groups but ideally also the flexible construction of various natural-product-like, polycyclic scaffolds from common precursors.     

Sparse representation approaches for the classification of high-dimensional biological data

Background

High-throughput genomic and proteomic data have important applications in medicine including prevention, diagnosis, treatment, and prognosis of diseases, and molecular biology, for example pathway identification. Many of such applications can be formulated to classification and dimension reduction problems in machine learning. There are computationally challenging issues with regards to accurately classifying such data, and which due to dimensionality, noise and redundancy, to name a few. The principle of sparse representation has been applied to analyzing high-dimensional biological data within the frameworks of clustering, classification, and dimension reduction approaches. However, the existing sparse representation methods are inefficient. The kernel extensions are not well addressed either. Moreover, the sparse representation techniques have not been comprehensively studied yet in bioinformatics.

Results

In this paper, a Bayesian treatment is presented on sparse representations. Various sparse coding and dictionary learning models are discussed. We propose fast parallel active-set optimization algorithm for each model. Kernel versions are devised based on their dimension-free property. These models are applied for classifying high-dimensional biological data.

Conclusions

In our experiment, we compared our models with other methods on both accuracy and computing time. It is shown that our models can achieve satisfactory accuracy, and their performance are very efficient.

     

Computational approaches to disease-gene prediction: rationale, classification and successes

The identification of genes involved in human hereditary diseases often requires the time-consuming and expensive examination of a great number of possible candidate genes, since genome-wide techniques such as linkage analysis and association studies frequently select many hundreds of 'positional' candidates. Even considering the positive impact of next-generation sequencing technologies, the prioritization of candidate genes may be an important step for disease-gene identification. In this paper we develop a basic classification scheme for computational approaches to disease-gene prediction and apply it to exhaustively review bioinformatics tools that have been developed for this purpose, focusing on conceptual aspects rather than technical detail and performance. Finally, we discuss some past successes obtained by computational approaches to illustrate their beneficial contribution to medical research.     

It is time to end the patenting of software

One of the most significant outcomes of genomics has been arapid increase in the rate that we as a community can generatedata on interesting biological systems. Rapid improvements intechnologies such as DNA microarrays and proteomics applicationshave produced a climate where the challenge is no longer collectinghigh quality data but rather managing and analyzing it. As wein the bioinformatics community have addressed this challenge,we have had to carefully consider the way in which the resultsof our intellectual efforts—the software tools that wedevelop—are made available to the wider research community.Increasingly, bioinformatics scientists are coming to call fordevelopment in an open source environment in which softwareis distributed with its underlying source code     

Penaeus monodon Dscam (PmDscam) has a highly diverse cytoplasmic tail and is the first membrane-bound shrimp Dscam to be reported

Down syndrome cell adhesion molecule (Dscam) seems likely to play a key role in the "alternative adaptive immunity" that has been reported in invertebrates. Dscam consists of a cytoplasmic tail that is involved in signal transduction and a hypervariable extracellular region that might use a pathogen recognition mechanism similar to that used by the vertebrate antibodies. In our previous paper, we isolated a unique tail-less form of Dscam from Litopenaeus vannamei. In this study, we report the first membrane-bound form of shrimp Dscam: PmDscam was isolated from Penaeus monodon, and it occurred in both membrane-bound and tail-less forms. Phylogenetic analysis showed that while the crustacean Dscams from shrimp and water flea did not share a single subclade, they were distinct from the invertebrate Dscam-like molecules and from the insecta Dscams. In the extracellular region, the variable regions of PmDscam were located in N-terminal Ig2, N-terminal Ig3 and the entire Ig7 domain. The PmDscam extracellular variants and transmembrane domain variants were produced by mutually exclusive alternative splicing events. The cytoplasmic tail variants were produced by exon inclusion/exclusion. Based on the genomic organization of Daphnia Dscam's cytoplasmic tail, we propose a model of how the shrimp Dscam genomic locus might use Type III polyadenylation to generate both the tail-less and membrane-bound forms.