Business Process Reengineering and Flexibility: A Case for Unification

Business process reengineering (BPR) offers a radical approach to improving the performance of an organization. However, although there have been successes BPR is recognized as a high-risk activity, prone to failure. There are a variety of reasons for this and this paper highlights one which is argued to be the lack of attention that BPR pays to flexibility and its inability to cope with a changing environment. The purpose of this article is to raise the issue of flexibility within BPR and an approach is taken that examines flexibility in other business functional areas, such as manufacturing, architecture, information systems, and organizational strategy, where there is an extensive literature that indicates the importance of flexibility. The lessons from these other areas are identified and some of the implications for BPR are highlighted. A number of proposals are made including the suggestion that a form of “flexibility analysis” be adopted as a stage in BPR projects. It is argued that this would help to move the focus of a BPR project away from the current requirements toward a longer term, more flexible, enduring set of requirements. Flexibility analysis also ensures analysis of the kinds of changes that might be required over time, and how such change could be accommodated in the reengineered processes.     

Teams and their Motivation for Business Process Reengineering: A Research Note

When business process reengineering (BPR) is undertaken, one of the requirements leading to its development and implementation is that of teams. There have not been many publications about the teams that are formed for undertaking BPR. This article addresses the theoretical issues surrounding such teams and attempts to provide an understanding of the role of motivation in such teams. Furthermore, an overview of the research process that is undertaken within the article is presented.     

Reliable B Cell Epitope Predictions: Impacts of Method Development and Improved Benchmarking

The interaction between antibodies and antigens is one of the most important immune system mechanisms for clearing infectious organisms from the host. Antibodies bind to antigens at sites referred to as B-cell epitopes. Identification of the exact location of B-cell epitopes is essential in several biomedical applications such as; rational vaccine design, development of disease diagnostics and immunotherapeutics. However, experimental mapping of epitopes is resource intensive making in silico methods an appealing complementary approach. To date, the reported performance of methods for in silico mapping of B-cell epitopes has been moderate. Several issues regarding the evaluation data sets may however have led to the performance values being underestimated: Rarely, all potential epitopes have been mapped on an antigen, and antibodies are generally raised against the antigen in a given biological context not against the antigen monomer. Improper dealing with these aspects leads to many artificial false positive predictions and hence to incorrect low performance values. To demonstrate the impact of proper benchmark definitions, we here present an updated version of the DiscoTope method incorporating a novel spatial neighborhood definition and half-sphere exposure as surface measure. Compared to other state-of-the-art prediction methods, Discotope-2.0 displayed improved performance both in cross-validation and in independent evaluations. Using DiscoTope-2.0, we assessed the impact on performance when using proper benchmark definitions. For 13 proteins in the training data set where sufficient biological information was available to make a proper benchmark redefinition, the average AUC performance was improved from 0.791 to 0.824. Similarly, the average AUC performance on an independent evaluation data set improved from 0.712 to 0.727. Our results thus demonstrate that given proper benchmark definitions, B-cell epitope prediction methods achieve highly significant predictive performances suggesting these tools to be a powerful asset in rational epitope discovery. The updated version of DiscoTope is available at www.cbs.dtu.dk/services/DiscoTope-2.0.     

Reengineering granulocyte colony-stimulating factor for enhanced stability

Granulocyte colony-stimulating factor is a long-chain cytokine that has both biological and therapeutic applications. It is involved in the production and maturation of neutrophilic progenitor cells and neutrophils and is administered to stimulate the production of white blood cells to reduce the risk of serious infection in immunocompromised patients. We have reengineered granulocyte colony-stimulating factor to improve the thermodynamic stability of the protein, focusing on enhancing the alpha-helical propensity of residues in the antiparallel 4-helix bundle of the protein. These redesigns resulted in proteins with substantially enhanced stability while retaining wild-type levels of biological activity, measured as the ability of the reengineered proteins to stimulate the proliferation of murine myeloid cells transfected with the granulocyte colony-stimulating factor receptor.     

Benchmarking secondary structure prediction for fold recognition

If secondary structure predictions are to be incorporated into fold recognition methods, an assessment of the effect of specific types of errors in predicted secondary structures on the sensitivity of fold recognition should be carried out. Here, we present a systematic comparison of different secondary structure prediction methods by measuring frequencies of specific types of error. We carry out an evaluation of the effect of specific types of error on secondary structure element alignment (SSEA), a baseline fold recognition method. The results of this evaluation indicate that missing out whole helix or strand elements, or predicting the wrong type of element, is more detrimental than predicting the wrong lengths of elements or overpredicting helix or strand. We also suggest that SSEA scoring is an effective method for assessing accuracy of secondary structure prediction and perhaps may also provide a more appropriate assessment of the "usefulness" and quality of predicted secondary structure, if secondary structure alignments are to be used in fold recognition.     

碱裂解法提取细菌质粒DNA的改良

碱裂解法是目前最为广泛应用的细菌质粒DNA的提取方法。但该法提取DNA所需时间较长,通常需要2h以上。为了快速提取质粒DNA,对常规碱裂法中溶液Ⅰ、Ⅱ、Ⅲ、RNA酶A及无水乙醇的反应时间由原来的5min,5min,10min,30min,10min分别缩短至5s,1min,5s,10min,5min。这种改良方法极大地缩短了DNA的提取时间,可在30min内完成整个DNA的制备,且制备的DNA可直接应用于进一步的酶切,连接及PCR等各种分子生物学分析。     

脯氨酸测定方法的改进

25mg·mL-1的酸性茚三酮溶液至少可以保存35 d,它与同体积脯氨酸充分反应的最大浓度为156μg·mL-1,当样品提取液的浓度大于100μg·mL-1时,需适当稀释.酸性茚三酮与脯氨酸充分显色的时间至少30 min沸水浴.     

A Phylogeny-Based Benchmarking Test for Orthology Inference Reveals the Limitations of Function-Based Validation

Accurate orthology prediction is crucial for many applications in the post-genomic era. The lack of broadly accepted benchmark tests precludes a comprehensive analysis of orthology inference. So far, functional annotation between orthologs serves as a performance proxy. However, this violates the fundamental principle of orthology as an evolutionary definition, while it is often not applicable due to limited experimental evidence for most species. Therefore, we constructed high quality "gold standard" orthologous groups that can serve as a benchmark set for orthology inference in bacterial species. Herein, we used this dataset to demonstrate 1) why a manually curated, phylogeny-based dataset is more appropriate for benchmarking orthology than other popular practices and 2) how it guides database design and parameterization through careful error quantification. More specifically, we illustrate how function-based tests often fail to identify false assignments, misjudging the true performance of orthology inference methods. We also examined how our dataset can instruct the selection of a “core” species repertoire to improve detection accuracy. We conclude that including more genomes at the proper evolutionary distances can influence the overall quality of orthology detection. The curated gene families, called Reference Orthologous Groups, are publicly available at http://eggnog.embl.de/orthobench2.     

Benchmarking a memetic algorithm for ordering microarray data

This work introduces a new algorithm for "gene ordering". Given a matrix of gene expression data values, the task is to find a permutation of the gene names list such that genes with similar expression patterns should be relatively close in the permutation. The algorithm is based on a combined approach that integrates a constructive heuristic with evolutionary and Tabu Search techniques in a single methodology. To evaluate the benefits of this method, we compared our results with the current outputs provided by several widely used algorithms in functional genomics. We also compared the results with our own hierarchical clustering method when used in isolation. We show that the use of images, corrupted with known levels of noise, helps to illustrate some aspects of the performance of the algorithms and provide a complementary benchmark for the analysis. The use of these images, with known high-quality solutions, facilitates in some cases the assessment of the methods and helps the software development, validation and reproducibility of results. We also propose two quantitative measures of performance for gene ordering. Using these measures, we make a comparison with probably the most used algorithm (due to Eisen and collaborators, PNAS 1998) using a microarray dataset available on the public domain (the complete yeast cell cycle dataset).     

双丙磷测定方法的改进

本文探讨了用氨基酸自动分析仪测定生物除草剂双丙磷的方法。结果表明,本方法能有效克服干扰,回收率为９７～１０２％。变异系数０．６９～１．０％,线性相关系数为０．９９９８。     

Benchmarking tools for the alignment of functional noncoding DNA

Background

Numerous tools have been developed to align genomic sequences. However, their relative performance in specific applications remains poorly characterized. Alignments of protein-coding sequences typically have been benchmarked against "correct" alignments inferred from structural data. For noncoding sequences, where such independent validation is lacking, simulation provides an effective means to generate "correct" alignments with which to benchmark alignment tools.

Results

Using rates of noncoding sequence evolution estimated from the genus Drosophila, we simulated alignments over a range of divergence times under varying models incorporating point substitution, insertion/deletion events, and short blocks of constrained sequences such as those found in cis-regulatory regions. We then compared "correct" alignments generated by a modified version of the ROSE simulation platform to alignments of the simulated derived sequences produced by eight pairwise alignment tools (Avid, BlastZ, Chaos, ClustalW, DiAlign, Lagan, Needle, and WABA) to determine the off-the-shelf performance of each tool. As expected, the ability to align noncoding sequences accurately decreases with increasing divergence for all tools, and declines faster in the presence of insertion/deletion evolution. Global alignment tools (Avid, ClustalW, Lagan, and Needle) typically have higher sensitivity over entire noncoding sequences as well as in constrained sequences. Local tools (BlastZ, Chaos, and WABA) have lower overall sensitivity as a consequence of incomplete coverage, but have high specificity to detect constrained sequences as well as high sensitivity within the subset of sequences they align. Tools such as DiAlign, which generate both local and global outputs, produce alignments of constrained sequences with both high sensitivity and specificity for divergence distances in the range of 1.25–3.0 substitutions per site.

Conclusion

For species with genomic properties similar to Drosophila, we conclude that a single pair of optimally diverged species analyzed with a high performance alignment tool can yield accurate and specific alignments of functionally constrained noncoding sequences. Further algorithm development, optimization of alignment parameters, and benchmarking studies will be necessary to extract the maximal biological information from alignments of functional noncoding DNA.

     

Benchmarking template selection and model quality assessment for high-resolution comparative modeling

Comparative modeling is presently the most accurate method of protein structure prediction. Previous experiments have shown the selection of the correct template to be of paramount importance to the quality of the final model. We have derived a set of 732 targets for which a choice of ten or more templates exist with 30-80% sequence identity and used this set to compare a number of possible methods for template selection: BLAST, PSI-BLAST, profile-profile alignment, HHpred HMM-HMM comparison, global sequence alignment, and the use of a model quality assessment program (MQAP). In addition, we have investigated the question of whether any structurally defined subset of the sequence could be used to predict template quality better than overall sequence similarity. We find that template selection by BLAST is sufficient in 75% of cases but that there are examples in which improvement (global RMSD 0.5 A or more) could be made. No significant improvement is found for any of the more sophisticated sequence-based methods of template selection at high sequence identities. A subset of 118 targets extending to the lowest levels of sequence similarity was examined and the HHpred and MQAP methods were found to improve ranking when available templates had 35-40% maximum sequence identity. Structurally defined subsets in general are found to be less discriminative than overall sequence similarity, with the coil residue subset performing equivalently to sequence similarity. Finally, we demonstrate that if models are built and model quality is assessed in combination with the sequence-template sequence similarity that a extra 7% of "best" models can be found.     

多糖和糖蛋白聚丙烯酰胺凝胶电泳染色方法的改进

对多糖聚丙烯酰胺凝胶电泳（PAGE）的缓冲系统进行了改进,尤其是多糖电泳后的染色方法的改进,得出一种操作简便、时间短、实验成本低的PAS染色法。