A branch and cut algorithm for the container shipping network design problem

The network design problem in liner shipping is of increasing importance in a strongly competitive market where potential cost reductions can influence market share and profits significantly. In this paper the network design and fleet assignment problems are combined into a mixed integer linear programming model minimizing the overall cost. To better reflect the real-life situation we take into account the cost of transhipment, a heterogeneous fleet, route dependent capacities, and butterfly routes. To the best of our knowledge it is the first time an exact solution method to the problem considers transhipment cost. The problem is solved with branch-and-cut using clover and transhipment inequalities. Computational results are reported for instances with up to 15 ports.     

Cooperative control of tumor suppressor genes by a network of oncogenic microRNAs

Individual microRNAs (miRNAs) have been implicated as oncogenes in experimental cancer models and their expression may affect clinical outcomes. To gain a more comprehensive view of miRNA action in leukemia, we analyzed miRNA expression patters in T-cell leukemia ALL (T-ALL) and cross-referenced the results with an unbiased genetic screen and computational analyses.1 We found that multiple microRNAs contribute to leukmogenesis and act as multi-targeted regulators of several tumor suppressor genes. The oncomirs form a network of overlapping and partially redundant interactions that stabilize the malignant phenotype though coordinate repression of cellular failsafe programs. The emerging network pattern of oncomir action is distinct from the notion of single oncogenic 'driver' mutation. We will discuss experimental, diagnostic and therapeutic implications of this concept of miRNA action in cancer.     

Universal DNA tag systems: a combinatorial design scheme.

Custom-designed DNA arrays offer the possibility of simultaneously monitoring thousands of hybridization reactions. These arrays show great potential for many medical and scientific applications, such as polymorphism analysis and genotyping. Relatively high costs are associated with the need to specifically design and synthesize problem-specific arrays. Recently, an alternative approach was suggested that utilizes fixed, universal arrays. This approach presents an interesting design problem-the arrays should contain as many probes as possible, while minimizing experimental errors caused by cross-hybridization. We use a simple thermodynamic model to cast this design problem in a formal mathematical framework. Employing new combinatorial ideas, we derive an efficient construction for the design problem and prove that our construction is near-optimal.     

Quality control in manufacturing oligo arrays: a combinatorial design approach.

The advent of the DNA microarray technology has brought with it the exciting possibility of simultaneously observing the expression levels of all genes in an organism. One such microarray technology, called "oligo arrays," manufactures short single strands of DNA (called probes) onto a glass surface using photolithography. An altered or missed step in such a manufacturing protocol can adversely affect all probes using this failed step and is in general impossible to disentangle from experimental variation when using such a defective array. The idea of designing special quality control probes to detect a failed step was first formulated by Hubbell and Pevzner (1999). We consider an alternative formulation of this problem and use a combinatorial design approach to solve it. Our results improve over prior work in guaranteeing coverage of all protocol steps and in being able to tolerate a greater number of unreliable probe intensities.     

Determinants of liposome partitioning in aqueous two-phase systems: Evaluation by means of a factorial design

This article evaluates the influence of five parameters on liposome partitioning in aqueous two-phase systems (ATPSs), composed of poly(ethyleneglycol) (PEG)/dextran (Dx), using the factorial experimental design together with a multiple regression. Mathematical models to quantify the influence of these parameters, individually and/or jointly, on liposome partitioning in ATPS were developed. The models were statistically tested and verified by experimentation. This approach was then used to define the conditions for the preferential accumulation of liposomes in the top PEG-rich phase. The models predicted a significant effect of liposome surface charge, PEG molecular weight, phase-forming polymer concentration, and phosphate ion concentration on the partition behavior of liposomes. For negatively charged liposomes, it was found that the smaller the molecular weight of PEG and polymer concentration and the larger the phosphate ion concentration, the greater the partition coefficient of the liposomes. No significant effect of pH, at the range of 6-8, on liposome partitioning was noted. This approach has led to the development of an optimal two-phase system where 90% of negatively charged liposomes accumulated in the PEG phase. In addition to the general scientific value of this research, it has a technological importance as ATPSs may be useful for removing the unentrapped drug from liposomes during their preparation for pharmaceutical applications. (c) 1996 John Wiley & Sons, Inc.     

Process optimization using combinatorial design principles: parallel synthesis and design of experiment methods

The use of parallel synthesis techniques with statistical design of experiment (DoE) methods is a powerful combination for the optimization of chemical processes. Advances in parallel synthesis equipment and easy to use software for statistical DoE have fueled a growing acceptance of these techniques in the pharmaceutical industry. As drug candidate structures become more complex at the same time that development timelines are compressed, these enabling technologies promise to become more important in the future.     

Development of a gas chromatography/mass spectrometry based metabolomics protocol by means of statistical experimental design

Metabolomics is a growing research field where new protocols are rapidly developed and new applications discovered. Common applications include biomarker discovery and elucidation of drug metabolism. However, the development of such protocols rarely includes a systematic optimization followed by validation with real samples. Here a GC/MS-based protocol using methoximation followed by silylation with N-tert-butyldimethylsilyl-N-methyltrifluoroacetamide (MTBSTFA) for analysis of blood plasma metabolites is thoroughly developed and optimized from derivatization to detection with statistical design of experiments (DOE). Validation was performed with blood plasma samples and proved the methodology to be efficient, rapid and reliable with a total of 51 analyses performed in 24 h, with linear responses, low detection limits and good precision. The obtained chromatograms were much cleaner, due to the absence of glucose overloading, and the data was found to drift less with MTBSTFA derivatisation than with MTBSTFA derivatisation.     

Computational design of auxotrophy-dependent microbial biosensors for combinatorial metabolic engineering experiments

Combinatorial approaches in metabolic engineering work by generating genetic diversity in a microbial population followed by screening for strains with improved phenotypes. One of the most common goals in this field is the generation of a high rate chemical producing strain. A major hurdle with this approach is that many chemicals do not have easy to recognize attributes, making their screening expensive and time consuming. To address this problem, it was previously suggested to use microbial biosensors to facilitate the detection and quantification of chemicals of interest. Here, we present novel computational methods to: (i) rationally design microbial biosensors for chemicals of interest based on substrate auxotrophy that would enable their high-throughput screening; (ii) predict engineering strategies for coupling the synthesis of a chemical of interest with the production of a proxy metabolite for which high-throughput screening is possible via a designed bio-sensor. The biosensor design method is validated based on known genetic modifications in an array of E. coli strains auxotrophic to various amino-acids. Predicted chemical production rates achievable via the biosensor-based approach are shown to potentially improve upon those predicted by current rational strain design approaches. (A Matlab implementation of the biosensor design method is available via http://www.cs.technion.ac.il/~tomersh/tools).     

Mini-review: combinatorial approaches for the design of novel coating systems

Combinatorial and high throughput experimental methods are being applied to the design and development of novel polymers and coatings used in a number of application areas. Methods have been developed for polymer synthesis and screening and for the development of polymer thin film and coating libraries and the screening of these libraries for key properties such as surface energy and modulus. Combinatorial and high throughput methods enable the efficient exploration of a large number of compositional variables over a wide range. In the development of coatings for use in the marine environment, the key challenge is in the development of screening methods that can predict good performance. A number of assays are under development that will permit the rapid screening of the interaction of coatings with representative marine organisms.     

In silico design of potent EGFR kinase inhibitors using combinatorial libraries

This paper is an attempt to design 4-anilinoquinazoline compounds having promising anticancer activities against epidermal growth factor (EGFR) kinase inhibition, using virtual combinatorial library approach. Partial least squares method has been applied for the development of a quantitative structure–activity relationship (QSAR) model based on training and test set approaches. The partial least squares model showed some interesting results in terms of internal and external predictability against EGFR kinase inhibition for such type of anilinoquinazoline derivatives. In virtual screening study, out of 4860 compounds in chemical library, 158 compounds were screened and finally, 10 compounds were selected as promising EGFR kinase inhibitors based on their predicted activities from the QSAR model. These derivatives were subjected to molecular docking study to investigate the mode of binding with the EGFR kinase, and the two compounds (ID 3639 and 3399) showing similar type of docking score and binding patterns with that of the existing drug molecules like erlotinib were finally reported.     

Principles of evolutionary learning design for a stochastic neural network

The authors develop principles for evolutionary learning typical of biological systems and demonstrate how these principles can be realized with a formal stochastic network.     

Suppression of the rayleigh-taylor instability of a low-density imploding liner by a longitudinal magnetic field

The possibility of suppressing the Rayleigh-Taylor instability in a low-density plasma, Π=ω _pi ² Δ²/c²?1 (where Δ is the thickness of the current-carrying slab), is investigated for the case in which the electron currents are much higher than the ion currents. The suppression of this instability in an imploding cylindrical liner by an axial external magnetic field \(B_{0z} \) is considered. It is shown that, for the instability to be suppressed, the external magnetic field \(B_{0z} \) should be stronger than the magnetic field B_0θ of the current flowing through the liner.