Fast Acquisition of (13)C NMR Spectra using the Steady-state Free Precession Sequence

In this paper, we show that the steady-state free precession sequence can be used to acquire (13)C high-resolution nuclear magnetic resonance spectra and applied to qualitative analysis. The analysis of brucine sample using this sequence with 60 degrees flip angle and time interval between pulses equal to 300 ms (acquisition time, 299.7 ms; recycle delay, 300 ms) resulted in spectrum with twofold enhancement in signal-to-noise ratio, when compared to standard (13)C sequence. This gain was better when a much shorter time interval between pulses (100 ms) was applied. The result obtained was more than fivefold enhancement in signal-to-noise ratio, equivalent to more than 20-fold reduction in total data recording time. However, this short time interval between pulses produces a spectrum with severe phase and truncation anomalies. We demonstrated that these anomalies can be minimized by applying an appropriate apodization function and plotting the spectrum in the magnitude mode.

Mining sequential causal patterns with user-specified skeletons in multi-sequence of event data

The approaches proposed in the past for discovering sequential patterns mainly focused on single sequential data. In the real world, however, some sequential patterns hide their essences among multi-sequential event data. It has been noted that knowledge discovery with either user-specified constraints, or templates, or skeletons is receiving wide attention because it is more efficient and avoids the tedious selection of useful patterns from the mass-produced results. In this paper, a novel pattern in multi-sequential event data that are correlated and its mining approach are presented. We call this pattern sequential causal pattern. A group of skeletons of sequential causal patterns, which may be specified by the user or generated by the program, are verified or mined by embedding them into the mining engine. Experiments show that this method, when applied to discovering the occurring regularities of a crop pest in a region, is successful in mining sequential causal patterns with user-specified skeletons in multi-sequential event data.

ANNODA: tool for integrating molecular-biological annotation data

Collecting, analyzing, and making Molecularbiological annotation data accessible in different public data sources is still an ongoing project. Integration of such data from these data sources might lead to valuable biological knowledge. There are numerous annotation data and only some of those are structured. The number and contents of related sources are continuously increasing. In addition, the existing data sources have their own storage structure and implementation. As a result, these could lead to a limitation in the combining of annotation. Here, we proposed a tool, called ANNODA, for integrating Molecular-biological annotation data. Unlike the past work on database interoperation in the bioinformatics community, this database design uses web-links which are very useful for interactive navigation and meanwhile it also supports automated large-scale analysis tasks.

Information integration in molecular bioscience

Integrating information in the molecular biosciences involves more than the cross-referencing of sequences or structures. Experimental protocols, results of computational analyses, annotations and links to relevant literature form integral parts of this information, and impart meaning to sequence or structure. In this review, we examine some existing approaches to integrating information in the molecular biosciences. We consider not only technical issues concerning the integration of heterogeneous data sources and the corresponding semantic implications, but also the integration of analytical results. Within the broad range of strategies for integration of data and information, we distinguish between platforms and developments. We discuss two current platforms and six current developments, and identify what we believe to be their strengths and limitations. We identify key unsolved problems in integrating information in the molecular biosciences, and discuss possible strategies for addressing them including semantic integration using ontologies, XML as a data model, and graphical user interfaces as integrative environments.

Molecular cloning of natriuretic peptides from the heart of reptiles : loss of ANP in diapsid reptiles and birds

Atrial natriuretic peptide (ANP) and B-type NP (BNP) are hormones involved in homeostatic control of body fluid and cardiovascular regulation. Both ANP and BNP have been cloned from the heart of mammals, amphibians, and teleost fishes, while an additional cardiac peptide, ventricular NP, has been found in selected species of teleost fish. However, in chicken, BNP is the primary cardiac peptide identified thus far. In contrast, the types of NP/s present in the reptilian heart are unknown, representing a considerable gap in our understanding of NP evolution. In the present study, we cloned and sequenced a BNP cDNA from the atria of representative species of reptile, including crocodile, lizard, snake, and tortoise. In addition, we cloned BNP from the pigeon atria. The reptilian and pigeon BNP cDNAs had ATTTA repeats in the 3′ untranslated region, as observed in all vertebrate BNP mRNAs. A high sequence homology was evident when comparing reptile and pigeon preproBNP with the previously identified chicken preproBNP. In particular, the predicted mature BNP-29 was identical between crocodile, tortoise, and chicken, with pigeon having a single amino acid substitution; lizard and snake BNP had seven and nine substitutions, respectively. Furthermore, an ANP cDNA could only be cloned from the tortoise atria. Since ANP was not isolated from the heart of any non-chelonian reptile and appears to be absent in birds, we propose that the ANP gene has been lost after branching of the turtles in the amniote line. This data provides new avenues for research on NP function in reptiles.

Manual on application of molecular tools in aquaculture and inland fisheries management. Part I : laboratory protocols, data management and analysis

The aim of this manual is to provide a comprehensive practical tool for the generation and analysis of genetic data for subsequent application in aquatic resources management in relation to genetic stock identification in inland fisheries and aquaculture. The material only covers general background on genetics in relation to aquaculture and fisheries resource management, the techniques and relevant methods of data analysis that are commonly used to address questions relating to genetic resource characterisation and population genetic analyses. No attempt is made to include applications of genetic improvement techniques e.g. selective breeding or producing genetically modified organisms (GMOs). The manual includes two ‘stand-alone’ parts, of which this is the second volume: Part 1 – Conceptual basis of population genetic approaches: will provide a basic foundation on genetics in general, and concepts of population genetics. Issues on the choices of molecular markers and project design are also discussed. Part 2 – Laboratory protocols, data management and analysis: will provide step-by-step protocols of the most commonly used molecular genetic techniques utilised in population genetics and systematic studies. In addition, a brief discussion and explanation of how these data are managed and analysed is also included. This manual is expected to enable NACA member country personnel to be trained to undertake molecular genetic studies in their own institutions, and as such is aimed at middle and higher level technical grades. The manual can also provide useful teaching material for specialised advanced level university courses in the region and postgraduate students. The manual has gone through two development/improvement stages. The initial material was tested at a regional workshop and at the second stage feedback from participants was used to improve the contents.