scispace - formally typeset
Search or ask a question
Institution

University of Minho

EducationBraga, Portugal
About: University of Minho is a education organization based out in Braga, Portugal. It is known for research contribution in the topics: Context (language use) & Population. The organization has 10585 authors who have published 34736 publications receiving 732436 citations. The organization is also known as: Universidade do Minho & UMinho.


Papers
More filters
Journal ArticleDOI
TL;DR: An expression cassette architecture for genetic elements controlling transcription and translation initiation in Escherichia coli is developed, demonstrating that arbitrary genes are reliably expressed to within twofold relative target expression windows with ∼93% reliability.
Abstract: An inability to reliably predict quantitative behaviors for novel combinations of genetic elements limits the rational engineering of biological systems. We developed an expression cassette architecture for genetic elements controlling transcription and translation initiation in Escherichia coli: transcription elements encode a common mRNA start, and translation elements use an overlapping genetic motif found in many natural systems. We engineered libraries of constitutive and repressor-regulated promoters along with translation initiation elements following these definitions. We measured activity distributions for each library and selected elements that collectively resulted in expression across a 1,000-fold observed dynamic range. We studied all combinations of curated elements, demonstrating that arbitrary genes are reliably expressed to within twofold relative target expression windows with ∼93% reliability. We expect the genetic element definitions validated here can be collectively expanded to create collections of public-domain standard biological parts that support reliable forward engineering of gene expression at genome scales.

724 citations

Journal ArticleDOI
TL;DR: The main chemical modifications of chitosan that have been proposed in the literature are reviewed and a wide range of derivatives with a broad range of applications are presented.

705 citations

Journal ArticleDOI
TL;DR: An overview on the available natural polymer/calcium phosphate nanocomposite materials, their design, and properties is presented.
Abstract: Tissue engineering and regenerative medicine has been providing exciting technologies for the development of functional substitutes aimed to repair and regenerate damaged tissues and organs. Inspired by the hierarchical nature of bone, nanostructured biomaterials are gaining a singular attention for tissue engineering, owing their ability to promote cell adhesion and proliferation, and hence new bone growth, compared with conventional microsized materials. Of particular interest are nanocomposites involving biopolymeric matrices and bioactive nanosized fillers. Biodegradability, high mechanical strength, and osteointegration and formation of ligamentous tissue are properties required for such materials. Biopolymers are advantageous due to their similarities with extracellular matrices, specific degradation rates, and good biological performance. By its turn, calcium phosphates possess favorable osteoconductivity, resorbability, and biocompatibility. Herein, an overview on the available natural polymer/calcium phosphate nanocomposite materials, their design, and properties is presented. Scaffolds, hydrogels, and fibers as biomimetic strategies for tissue engineering, and processing methodologies are described. The specific biological properties of the nanocomposites, as well as their interaction with cells, including the use of bioactive molecules, are highlighted. Nanocomposites in vivo studies using animal models are also reviewed and discussed.

691 citations

Journal ArticleDOI
01 Jun 2014
TL;DR: A data mining approach to predict the success of telemarketing calls for selling bank long-term deposits in Portuguese retail bank was addressed, with data collected from 2008 to 2013, thus including the effects of the recent financial crisis.
Abstract: We propose a data mining (DM) approach to predict the success of telemarketing calls for selling bank long-term deposits. A Portuguese retail bank was addressed, with data collected from 2008 to 2013, thus including the effects of the recent financial crisis. We analyzed a large set of 150 features related with bank client, product and social-economic attributes. A semi-automatic feature selection was explored in the modeling phase, performed with the data prior to July 2012 and that allowed to select a reduced set of 22 features. We also compared four DM models: logistic regression, decision trees (DTs), neural network (NN) and support vector machine. Using two metrics, area of the receiver operating characteristic curve (AUC) and area of the LIFT cumulative curve (ALIFT), the four models were tested on an evaluation set, using the most recent data (after July 2012) and a rolling window scheme. The NN presented the best results (AUC = 0.8 and ALIFT = 0.7), allowing to reach 79% of the subscribers by selecting the half better classified clients. Also, two knowledge extraction methods, a sensitivity analysis and a DT, were applied to the NN model and revealed several key attributes (e.g., Euribor rate, direction of the call and bank agent experience). Such knowledge extraction confirmed the obtained model as credible and valuable for telemarketing campaign managers.

673 citations

Journal ArticleDOI
TL;DR: This work received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement no.
Abstract: This work received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement no. REGPOT-CT2012-316331-POLARIS. The work was also funded by FEDER through the Competitive Factors Operational Program (COMPETE) and by National funds through the Portuguese Foundation for Science and Technology (FCT) in the scope of the projects PTDC/FIS/115048/2009 and PTDC/CTM-BIO/1814/2012. The authors gratefully acknowledge Dr. Luca Gasperini (3B's Research Group, University of Minho, Portugal) for his help with the figures.

673 citations


Authors

Showing all 10921 results

NameH-indexPapersCitations
A. Gomes1501862113951
Kazuhiko Hara1411956107697
Stefano Giagu1391651101569
Georges Azuelos134129490690
Fumihiko Ukegawa133149294465
Luis M. Liz-Marzán13261661684
Francesco Lacava130104279680
Jozsef Toth130115186193
Monica Verducci12989676002
Andrea Messina12893975409
Rostislav Konoplich12881173790
Michel Vetterli12890176064
Nuno Filipe Castro12896076945
Hideki Okawa12783973603
Nazim Huseynov12683372648
Network Information
Related Institutions (5)
University of Porto
64.5K papers, 1.5M citations

95% related

University of Toulouse
53.2K papers, 1.3M citations

90% related

Ghent University
111K papers, 3.7M citations

90% related

University of Granada
59.2K papers, 1.4M citations

90% related

Eindhoven University of Technology
52.9K papers, 1.5M citations

90% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023129
2022480
20212,659
20202,640
20192,505
20182,450