Random subwindows and extremely randomized trees for image classification in cell biology

Background: With the improvements in biosensors and high-throughput image acquisition technologies, life science laboratories are able to perform an increasing number of experiments that involve the generation of a large amount of images at different imaging modalities/scales. It stresses the need for computer vision methods that automate image classification tasks. Results: We illustrate the potential of our image classification method in cell biology by evaluating it on four datasets of images related to protein distributions or subcellular localizations, and red-blood cell shapes. Accuracy results are quite good without any specific pre-processing neither domain knowledge incorporation. The method is implemented in Java and available upon request for evaluation and research purpose. Conclusion: Our method is directly applicable to any image classification problems. We foresee the use of this automatic approach as a baseline method and first try on various biological image classification problems

Bioinformatics: A Way Forward to Explore “Plant Omics”

Bioinformatics, a computer-assisted science aiming at managing a huge volume of genomic data, is an emerging discipline that combines the power of computers, mathematical algorithms, and statistical concepts to solve multiple genetic/biological puzzles. This science has progressed parallel to the evolution of genome-sequencing tools, for example, the next-generation sequencing technologies, that resulted in arranging and analyzing the genome-sequencing information of large genomes. Synergism of “plant omics” and bioinformatics set a firm foundation for deducing ancestral karyotype of multiple plant families, predicting genes, etc. Second, the huge genomic data can be assembled to acquire maximum information from a voluminous “omics” data. The science of bioinformatics is handicapped due to lack of appropriate computational procedures in assembling sequencing reads of the homologs occurring in complex genomes like cotton (2n = 4x = 52), wheat (2n = 6x = 42), etc., and shortage of multidisciplinary-oriented trained manpower. In addition, the rapid expansion of sequencing data restricts the potential of acquisitioning, storing, distributing, and analyzing the genomic information. In future, inventions of high-tech computational tools and skills together with improved biological expertise would provide better insight into the genomes, and this information would be helpful in sustaining crop productivities on this planet

Comparison of trace metal bioavailabilities in European coastal waters using mussels from Mytilus edulis

Mussels from Mytilus edulis complex were used as biomonitors of the trace metals Fe, Mn, Pb, Zn, and Cu at 17 sampling sites to assess the relative bioavailability of metals in coastal waters around the European continent. Because accumulated metal concentrations in a given area can differ temporally, data were corrected for the effect of season before large-scale spatial comparisons were made. The highest concentration of Fe was noted in the North Sea and of Mn in the Baltic. Increased tissue concentrations of Pb were recorded in the mussels from the Bay of Biscay and the Baltic Sea. Low concentrations of metals were determined in the mussels from the Mediterranean Sea and the Northern Baltic. Relatively low geographic variations of Cu and Zn indicate that mussels are able to partially regulate accumulated body concentrations, which means Cu and Zn are, to some extent, independent of environmental concentrations

Emerging Vaccine Informatics

Vaccine informatics is an emerging research area that focuses on development and applications of bioinformatics methods that can be used to facilitate every aspect of the preclinical, clinical, and postlicensure vaccine enterprises. Many immunoinformatics algorithms and resources have been developed to predict T- and B-cell immune epitopes for epitope vaccine development and protective immunity analysis. Vaccine protein candidates are predictable in silico from genome sequences using reverse vaccinology. Systematic transcriptomics and proteomics gene expression analyses facilitate rational vaccine design and identification of gene responses that are correlates of protection in vivo. Mathematical simulations have been used to model host-pathogen interactions and improve vaccine production and vaccination protocols. Computational methods have also been used for development of immunization registries or immunization information systems, assessment of vaccine safety and efficacy, and immunization modeling. Computational literature mining and databases effectively process, mine, and store large amounts of vaccine literature and data. Vaccine Ontology (VO) has been initiated to integrate various vaccine data and support automated reasoning

Evolutionary Insights into the Enzymes involved in the Biosynthesis of the Volatile Organic Compounds Isoprene and Pinene in Plants

Volatile organic compounds (often abbreviated as VOCs) are emitted as secondary metabolites by plants, and contribute to a wide range of ecological processes, owing to their pivotal role in plant interactions with biotic and abiotic variables. As a result, they differ greatly between species and explain disparities in ecological strategy. In an effort to comprehend their genesis and assess potential evolutionary trends, this work probes into the enzymatic pathways that lead to their synthesis. Correspondingly, we adopt and propose an in-silico approach to analyze connections between the species evolution and the gene evolution of two major plant volatile organic compounds. We lay focus on isoprene and pinene, volatile organic compounds synthesized by two common yet compartmentally isolated pathways - the methylerythritol phosphate (MEP) pathway and the mevalonic acid (MVA) pathway, respectively. Analyses of gene-specific and protein-specific phylogenetic trees of the enzymes involved in these pathways thereby indicate a mixed trend in the evolution as per the APG IV (Angiosperm Phylogeny Group IV) system. These results and the in-silico pipeline thus provide us with future opportunities to explore different networks of plant communication for a holistic understanding of intraspecific and interspecific interactions in different natural ecosystems

Identification of differentially accumulated proteins associated with embryogenic and non-embryogenic calli in saffron (Crocus sativus L.)

<p>Abstract</p> <p>Background</p> <p>Somatic embryogenesis (SE) is a complex biological process that occurs under inductive conditions and causes fully differentiated cells to be reprogrammed to an embryo like state. In order to get a better insight about molecular basis of the SE in <it>Crocus sativus </it>L. and to characterize differentially accumulated proteins during the process, a proteomic study based on two-dimensional gel electrophoresis and matrix-assisted laser desorption/ionization time of flight mass spectrometry has been carried out.</p> <p>Results</p> <p>We have compared proteome profiles of non-embryogenic and embryogenic calli with native corm explants. Total soluble proteins were phenol-extracted and loaded on 18 cm IPG strips for the first dimension and 11.5% sodium dodecyl sulfate-polyacrylamide gels for the second dimension. Fifty spots with more than 1.5-fold change in abundance were subjected to mass spectrometry analysis for further characterization. Among them 36 proteins could be identified, which are classified into defense and stress response, protein synthesis and processing, carbohydrate and energy metabolism, secondary metabolism, and nitrogen metabolism.</p> <p>Conclusion</p> <p>Our results showed that diverse cellular and molecular processes were affected during somatic to embryogenic transition. Differential proteomic analysis suggests a key role for ascorbate metabolism during early stage of SE, and points to the possible role of ascorbate-glutathione cycle in establishing somatic embryos.</p

Full Text and Figure Display Improves Bioscience Literature Search

When reading bioscience journal articles, many researchers focus attention on the figures and their captions. This observation led to the development of the BioText literature search engine [1], a freely available Web-based application that allows biologists to search over the contents of Open Access Journals, and see figures from the articles displayed directly in the search results. This article presents a qualitative assessment of this system in the form of a usability study with 20 biologist participants using and commenting on the system. 19 out of 20 participants expressed a desire to use a bioscience literature search engine that displays articles' figures alongside the full text search results. 15 out of 20 participants said they would use a caption search and figure display interface either frequently or sometimes, while 4 said rarely and 1 said undecided. 10 out of 20 participants said they would use a tool for searching the text of tables and their captions either frequently or sometimes, while 7 said they would use it rarely if at all, 2 said they would never use it, and 1 was undecided. This study found evidence, supporting results of an earlier study, that bioscience literature search systems such as PubMed should show figures from articles alongside search results. It also found evidence that full text and captions should be searched along with the article title, metadata, and abstract. Finally, for a subset of users and information needs, allowing for explicit search within captions for figures and tables is a useful function, but it is not entirely clear how to cleanly integrate this within a more general literature search interface. Such a facility supports Open Access publishing efforts, as it requires access to full text of documents and the lifting of restrictions in order to show figures in the search interface

The role of cooperation in bacterial ecology and evolution

Bacteria can perform a range of cooperative behaviours, yet the significance of these cooperative behaviours in bacterial ecology and evolution is a burgeoning research area. In this thesis, I use a comparative genomics approach to elucidate the impact of cooperation on bacterial ecological and evolutionary processes. Specifically, I: (i) probe the effects of cooperation on the evolution of bacterial niche breadth; (ii) investigate the relationship between horizontal gene transfer and bacterial cooperation, with a specific emphasis on the interplay between gene connectivity and sociality in determining gene transfer potential. Additionally, I expand the scope by examining how ecological determinants and genomic characteristics shape the evolution of bacterial growth rates. In summary, this thesis offers novel perspectives on bacterial ecology and evolution through the lens of bacterial cooperation