Estimating and evaluating the statistics of gapped local-alignment scores

We present a novel maximum-likelihood-based algorithm for estimating the distribution of alignment scores from the scores of unrelated sequences in a database search. Using a new method for measuring the accuracy of p-values, we show that our maximum-likelihood-based algorithm is more accurate than existing regression-based and lookup table methods. We explore a more sophisticated way of modeling and estimating the score distributions (using a two-component mixture model and expectation maximization), but conclude that this does not improve significantly over simply ignoring scores with small E-values during estimation. Finally, we measure the classification accuracy of p-values estimated in different ways and observe that inaccurate p-values can, somewhat paradoxically, lead to higher classification accuracy. We explain this paradox and argue that statistical accuracy, not classification accuracy, should be the primary criterion in comparisons of similarity search methods that return p-values that adjust for target sequence length.

Direct multisearch for multiobjective optimization

In practical applications of optimization it is common to have several conflicting objective functions to optimize. Frequently, these functions are subject to noise or can be of black-box type, preventing the use of derivative-based techniques. We propose a novel multiobjective derivative-free methodology, calling it direct multisearch (DMS), which does not aggregate any of the objective functions. Our framework is inspired by the search/poll paradigm of direct-search methods of directional type and uses the concept of Pareto dominance to maintain a list of nondominated points (from which the new iterates or poll centers are chosen). The aim of our method is to generate as many points in the Pareto front as possible from the polling procedure itself, while keeping the whole framework general enough to accommodate other disseminating strategies, in particular, when using the (here also) optional search step. DMS generalizes to multiobjective optimization (MOO) all direct-search methods of directional type. We prove under the common assumptions used in direct search for single objective optimization that at least one limit point of the sequence of iterates generated by DMS lies in (a stationary form of) the Pareto front. However, extensive computational experience has shown that our methodology has an impressive capability of generating the whole Pareto front, even without using a search step. Two by-products of this paper are (i) the development of a collection of test problems for MOO and (ii) the extension of performance and data profiles to MOO, allowing a comparison of several solvers on a large set of test problems, in terms of their efficiency and robustness to determine Pareto fronts.

Derivative-free nonlinear optimization filter simplex

The filter method is a technique for solving nonlinear programming problems. The filter algorithm has two phases in each iteration. The first one reduces a measure of infeasibility, while in the second the objective function value is reduced. In real optimization problems, usually the objective function is not differentiable or its derivatives are unknown. In these cases it becomes essential to use optimization methods where the calculation of the derivatives or the verification of their existence is not necessary: direct search methods or derivative-free methods are examples of such techniques. In this work we present a new direct search method, based on simplex methods, for general constrained optimization that combines the features of simplex and filter methods. This method neither computes nor approximates derivatives, penalty constants or Lagrange multipliers.

Improvement of a filters method in a derivative free optimization

Constraints nonlinear optimization problems can be solved using penalty or barrier functions. This strategy, based on solving the problems without constraints obtained from the original problem, have shown to be e ective, particularly when used with direct search methods. An alternative to solve the previous problems is the lters method. The lters method introduced by Fletcher and Ley er in 2002, , has been widely used to solve problems of the type mentioned above. These methods use a strategy di erent from the barrier or penalty functions. The previous functions de ne a new one that combine the objective function and the constraints, while the lters method treat optimization problems as a bi-objective problems that minimize the objective function and a function that aggregates the constraints. Motivated by the work of Audet and Dennis in 2004, using lters method with derivative-free algorithms, the authors developed works where other direct search meth- ods were used, combining their potential with the lters method. More recently. In a new variant of these methods was presented, where it some alternative aggregation restrictions for the construction of lters were proposed. This paper presents a variant of the lters method, more robust than the previous ones, that has been implemented with a safeguard procedure where values of the function and constraints are interlinked and not treated completely independently.

Node adaptation for global collocation with radial basis functions using direct multisearch for multiobjective optimization

Meshless methods are used for their capability of producing excellent solutions without requiring a mesh, avoiding mesh related problems encountered in other numerical methods, such as finite elements. However, node placement is still an open question, specially in strong form collocation meshless methods. The number of used nodes can have a big influence on matrix size and therefore produce ill-conditioned matrices. In order to optimize node position and number, a direct multisearch technique for multiobjective optimization is used to optimize node distribution in the global collocation method using radial basis functions. The optimization method is applied to the bending of isotropic simply supported plates. Using as a starting condition a uniformly distributed grid, results show that the method is capable of reducing the number of nodes in the grid without compromising the accuracy of the solution. (C) 2013 Elsevier Ltd. All rights reserved.

Integrating protein structural information

Dissertação apresentada para obtenção de Grau de Doutor em Bioquímica,Bioquímica Estrutural, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Multiobjective optimization for node adaptation in the analysis of composite plates using a meshless collocation method

The bending of simply supported composite plates is analyzed using a direct collocation meshless numerical method. In order to optimize node distribution the Direct MultiSearch (DMS) for multi-objective optimization method is applied. In addition, the method optimizes the shape parameter in radial basis functions. The optimization algorithm was able to find good solutions for a large variety of nodes distribution.

Híper-heurísticas com aprendizagem

A otimização nos sistemas de suporte à decisão atuais assume um carácter fortemente interdisciplinar relacionando-se com a necessidade de integração de diferentes técnicas e paradigmas na resolução de problemas reais complexos, sendo que a computação de soluções ótimas em muitos destes problemas é intratável. Os métodos de pesquisa heurística são conhecidos por permitir obter bons resultados num intervalo temporal aceitável. Muitas vezes, necessitam que a parametrização seja ajustada de forma a permitir obter bons resultados. Neste sentido, as estratégias de aprendizagem podem incrementar o desempenho de um sistema, dotando-o com a capacidade de aprendizagem, por exemplo, qual a técnica de otimização mais adequada para a resolução de uma classe particular de problemas, ou qual a parametrização mais adequada de um dado algoritmo num determinado cenário. Alguns dos métodos de otimização mais usados para a resolução de problemas do mundo real resultaram da adaptação de ideias de várias áreas de investigação, principalmente com inspiração na natureza - Meta-heurísticas. O processo de seleção de uma Meta-heurística para a resolução de um dado problema é em si um problema de otimização. As Híper-heurísticas surgem neste contexto como metodologias eficientes para selecionar ou gerar heurísticas (ou Meta-heurísticas) na resolução de problemas de otimização NP-difícil. Nesta dissertação pretende-se dar uma contribuição para o problema de seleção de Metaheurísticas respetiva parametrização. Neste sentido é descrita a especificação de uma Híperheurística para a seleção de técnicas baseadas na natureza, na resolução do problema de escalonamento de tarefas em sistemas de fabrico, com base em experiência anterior. O módulo de Híper-heurística desenvolvido utiliza um algoritmo de aprendizagem por reforço (QLearning), que permite dotar o sistema da capacidade de seleção automática da Metaheurística a usar no processo de otimização, assim como a respetiva parametrização. Finalmente, procede-se à realização de testes computacionais para avaliar a influência da Híper- Heurística no desempenho do sistema de escalonamento AutoDynAgents. Como conclusão genérica, é possível afirmar que, dos resultados obtidos é possível concluir existir vantagem significativa no desempenho do sistema quando introduzida a Híper-heurística baseada em QLearning.

Adaptive Penalty and Barrier function based on Fuzzy Logic

Optimization methods have been used in many areas of knowledge, such as Engineering, Statistics, Chemistry, among others, to solve optimization problems. In many cases it is not possible to use derivative methods, due to the characteristics of the problem to be solved and/or its constraints, for example if the involved functions are non-smooth and/or their derivatives are not know. To solve this type of problems a Java based API has been implemented, which includes only derivative-free optimization methods, and that can be used to solve both constrained and unconstrained problems. For solving constrained problems, the classic Penalty and Barrier functions were included in the API. In this paper a new approach to Penalty and Barrier functions, based on Fuzzy Logic, is proposed. Two penalty functions, that impose a progressive penalization to solutions that violate the constraints, are discussed. The implemented functions impose a low penalization when the violation of the constraints is low and a heavy penalty when the violation is high. Numerical results, obtained using twenty-eight test problems, comparing the proposed Fuzzy Logic based functions to six of the classic Penalty and Barrier functions are presented. Considering the achieved results, it can be concluded that the proposed penalty functions besides being very robust also have a very good performance.

Estudo de soluções de otimização para edifícios de balanço energético nulo

Dissertação para obtenção do Grau de Mestre em Engenharia Civil – Perfil de Construção

Development of an intelligent earthwork optimization system

Tese de Doutoramento em Engenharia Civil.

Acetylcholinesterase inhibitor treatment for myasthenia gravis.

BACKGROUND: In myasthenia gravis, antibody-mediated blockade of acetylcholine receptors at the neuromuscular junction abolishes the naturally occurring 'safety factor' of synaptic transmission. Acetylcholinesterase inhibitors provide temporary symptomatic treatment of muscle weakness but there is controversy about their long-term efficacy, dosage and side effects. This is the second update of a review published in The Cochrane Library Issue 2, 2011. OBJECTIVES: To evaluate the efficacy of acetylcholinesterase inhibitors in all forms of myasthenia gravis. SEARCH METHODS: On 8 July 2014 we searched the Cochrane Neuromuscular Disease Group Specialized Register, CENTRAL, MEDLINE and EMBASE for randomised controlled trials and quasi-randomised controlled trials regarding usage of acetylcholinesterase inhibitors in myasthenia gravis. Two authors scanned the articles for any study eligible for inclusion. We also contacted the authors and known experts in the field to identify additional published or unpublished data and searched clinical trials registries for ongoing trials. SELECTION CRITERIA: The types of studies were randomised or quasi-randomised trials. Participants were myasthenia gravis patients diagnosed by an internationally accepted definition. The intervention was treatment with any form of acetylcholinesterase inhibitor. Types of outcome measures Primary outcome measureImprovement in the presenting symptoms within one to 14 days of the start of treatment. Secondary outcome measures(1) Improvement in the presenting symptoms more than 14 days after the start of treatment.(2) Change in impairment measured by a recognised and preferably validated scale, such as the quantitative myasthenia gravis score, within one to 14 days and more than 14 days after the start of treatment.(3) Myasthenia Gravis Association of America post-intervention status more than 14 days after start of treatment.(4) Adverse events including muscarinic side effects. DATA COLLECTION AND ANALYSIS: One author (MMM) extracted the data, which were checked by a second author. We contacted study authors for extra information and collected data on adverse effects from the trials. MAIN RESULTS: We did not find any large randomised or quasi-randomised trials of acetylcholinesterase inhibitors in generalised myasthenia gravis either for the first version of this review or this update. One cross-over randomised trial using intranasal neostigmine in a total of 10 participants was only available as an abstract. It included three participants with ocular myasthenia gravis and seven with generalised myasthenia gravis. Symptoms of myasthenia gravis (measured as improvement in at least one muscle function) improved in nine of the 10 participants after the two-week neostigmine treatment phase. No participant improved after the placebo phase. Lack of detail in the report meant that the risk of bias was unclear. Adverse events were minor. AUTHORS' CONCLUSIONS: Except for one small and inconclusive trial of intranasal neostigmine, no other randomised controlled trials have been conducted on the use of acetylcholinesterase inhibitors in myasthenia gravis. The response to acetylcholinesterase inhibitors in observational studies is so clear that a randomised controlled trial depriving participants in a placebo arm of treatment would be difficult to justify.

trEST, trGEN and Hits: access to databases of predicted protein sequences.

High throughput genome (HTG) and expressed sequence tag (EST) sequences are currently the most abundant nucleotide sequence classes in the public database. The large volume, high degree of fragmentation and lack of gene structure annotations prevent efficient and effective searches of HTG and EST data for protein sequence homologies by standard search methods. Here, we briefly describe three newly developed resources that should make discovery of interesting genes in these sequence classes easier in the future, especially to biologists not having access to a powerful local bioinformatics environment. trEST and trGEN are regularly regenerated databases of hypothetical protein sequences predicted from EST and HTG sequences, respectively. Hits is a web-based data retrieval and analysis system providing access to precomputed matches between protein sequences (including sequences from trEST and trGEN) and patterns and profiles from Prosite and Pfam. The three resources can be accessed via the Hits home page (http://hits. isb-sib.ch).

Recombinant human insulin-like growth factor I (rhIGF-I) for the treatment of amyotrophic lateral sclerosis/motor neuron disease.

BACKGROUND: Recombinant human insulin-like growth factor I (rhIGF-I) is a possible disease modifying therapy for amyotrophic lateral sclerosis (ALS, which is also known as motor neuron disease (MND)). OBJECTIVES: To examine the efficacy of rhIGF-I in affecting disease progression, impact on measures of functional health status, prolonging survival and delaying the use of surrogates (tracheostomy and mechanical ventilation) to sustain survival in ALS. Occurrence of adverse events was also reviewed. SEARCH METHODS: We searched the Cochrane Neuromuscular Disease Group Specialized Register (21 November 2011), CENTRAL (2011, Issue 4), MEDLINE (January 1966 to November 2011) and EMBASE (January 1980 to November 2011) and sought information from the authors of randomised clinical trials and manufacturers of rhIGF-I. SELECTION CRITERIA: We considered all randomised controlled clinical trials involving rhIGF-I treatment of adults with definite or probable ALS according to the El Escorial Criteria. The primary outcome measure was change in Appel Amyotrophic Lateral Sclerosis Rating Scale (AALSRS) total score after nine months of treatment and secondary outcome measures were change in AALSRS at 1, 2, 3, 4, 5, 6, 7, 8, 9 months, change in quality of life (Sickness Impact Profile scale), survival and adverse events. DATA COLLECTION AND ANALYSIS: Each author independently graded the risk of bias in the included studies. The lead author extracted data and the other authors checked them. We generated some missing data by making ruler measurements of data in published graphs. We collected data about adverse events from the included trials. MAIN RESULTS: We identified three randomised controlled trials (RCTs) of rhIGF-I, involving 779 participants, for inclusion in the analysis. In a European trial (183 participants) the mean difference (MD) in change in AALSRS total score after nine months was -3.30 (95% confidence interval (CI) -8.68 to 2.08). In a North American trial (266 participants), the MD after nine months was -6.00 (95% CI -10.99 to -1.01). The combined analysis from both RCTs showed a MD after nine months of -4.75 (95% CI -8.41 to -1.09), a significant difference in favour of the treated group. The secondary outcome measures showed non-significant trends favouring rhIGF-I. There was an increased risk of injection site reactions with rhIGF-I (risk ratio 1.26, 95% CI 1.04 to 1.54). . A second North American trial (330 participants) used a novel primary end point involving manual muscle strength testing. No differences were demonstrated between the treated and placebo groups in this study. All three trials were at high risk of bias. AUTHORS' CONCLUSIONS: Meta-analysis revealed a significant difference in favour of rhIGF-I treatment; however, the quality of the evidence from the two included trials was low. A third study showed no difference between treatment and placebo. There is no evidence for increase in survival with IGF1. All three included trials were at high risk of bias.

Vascular-endothelial-growth-factor (VEGF) targeting therapies for endocrine refractory or resistant metastatic breast cancer.

BACKGROUND: Vascular-endothelial-growth-factor (VEGF) is a key mediator of angiogenesis. VEGF-targeting therapies have shown significant benefits and been successfully integrated in routine clinical practice for other types of cancer, such as metastatic colorectal cancer. By contrast, individual trial results in metastatic breast cancer (MBC) are highly variable and their value is controversial. OBJECTIVES: To evaluate the benefits (in progression-free survival (PFS) and overall survival (OS)) and harms (toxicity) of VEGF-targeting therapies in patients with hormone-refractory or hormone-receptor negative metastatic breast cancer. SEARCH METHODS: Searches of CENTRAL, MEDLINE, EMBASE, the Cochrane Breast Cancer Group's Specialised Register, registers of ongoing trials and proceedings of conferences were conducted in January and September 2011, starting in 2000. Reference lists were scanned and members of the Cochrane Breast Cancer Group, experts and manufacturers of relevant drug were contacted to obtain further information. No language restrictions were applied. SELECTION CRITERIA: Randomised controlled trials (RCTs) to evaluate treatment benefit and non-randomised studies in the routine oncology practice setting to evaluate treatment harms. DATA COLLECTION AND ANALYSIS: We performed data collection and analysis according to the published protocol. Individual patient data was sought but not provided. Therefore, the meta-analysis had to be based on published data. Summary statistics for the primary endpoint (PFS) were hazard ratios (HRs). MAIN RESULTS: We identified seven RCTs, one register, and five ongoing trials from a total of 347 references. The published trials for VEGF-targeting drugs in MBC were limited to bevacizumab. Four trials, including a total of 2886 patients, were available for the comparison of first-line chemotherapy, with versus without bevacizumab. PFS (HR 0.67; 95% confidence interval (CI) 0.61 to 0.73) and response rate were significantly better for patients treated with bevacizumab, with moderate heterogeneity regarding the magnitude of the effect on PFS. For second-line chemotherapy, a smaller, but still significant benefit in terms of PFS could be demonstrated for patients treated with bevacizumab (HR 0.85; 95% CI 0.73 to 0.98), as well as a benefit in tumour response. However, OS did not differ significantly, neither in first- (HR 0.93; 95% CI 0.84 to 1.04), nor second-line therapy (HR 0.98; 95% CI 0.83 to 1.16). Quality of life (QoL) was evaluated in four trials but results were published for only two of these with no relevant impact. Subgroup analysis stated a significant greater benefit for patients with previous (taxane) chemotherapy and patients with hormone-receptor negative status. Regarding toxicity, data from RCTs and registry data were consistent and in line with the known toxicity profile of bevacizumab. While significantly higher rates of adverse events (AEs) grade III/IV (odds ratio (OR) 1.77; 95% CI 1.44 to 2.18) and serious adverse events (SAEs) (OR 1.41; 95% CI 1.13 to 1.75) were observed in patients treated with bevacizumab, rates of treatment-related deaths were lower in patients treated with bevacizumab (OR 0.60; 95% CI 0.36 to 0.99). AUTHORS' CONCLUSIONS: The overall patient benefit from adding bevacizumab to first- and second-line chemotherapy in metastatic breast cancer can at best be considered as modest. It is dependent on the type of chemotherapy used and limited to a prolongation of PFS and response rates in both first- and second-line therapy, both surrogate parameters. In contrast, bevacizumab has no significant impact on the patient-related secondary outcomes of OS or QoL, which indicate a direct patient benefit. For this reason, the clinical value of bevacizumab for metastatic breast cancer remains controversial.