Publications

2015

The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans

Authors
Ardlie, KG; DeLuca, DS; Segrè, AV; Sullivan, TJ; Young, TR; Gelfand, ET; Trowbridge, CA; Maller, JB; Tukiainen, T; Lek, M; Ward, LD; Kheradpour, P; Iriarte, B; Meng, Y; Palmer, CD; Esko, T; Winckler, W; Hirschhorn, JN; Kellis, M; MacArthur, DG; Getz, G; Shabalin, AA; Li, G; Zhou, YH; Nobel, AB; Rusyn, I; Wright, FA; Lappalainen, T; Ferreira, PG; Ongen, H; Rivas, MA; Battle, A; Mostafavi, S; Monlong, J; Sammeth, M; Melé, M; Reverter, F; Goldmann, JM; Koller, D; Guigó, R; McCarthy, MI; Dermitzakis, ET; Gamazon, ER; Im, HK; Konkashbaev, A; Nicolae, DL; Cox, NJ; Flutre, T; Wen, X; Stephens, M; Pritchard, JK; Tu, Z; Zhang, B; Huang, T; Long, Q; Lin, L; Yang, J; Zhu, J; Liu, J; Brown, A; Mestichelli, B; Tidwell, D; Lo, E; Salvatore, M; Shad, S; Thomas, JA; Lonsdale, JT; Moser, MT; Gillard, BM; Karasik, E; Ramsey, K; Choi, C; Foster, BA; Syron, J; Fleming, J; Magazine, H; Hasz, R; Walters, GD; Bridge, JP; Miklos, M; Sullivan, S; Barker, LK; Traino, HM; Mosavel, M; Siminoff, LA; Valley, DR; Rohrer, DC; Jewell, SD; Branton, PA; Sobin, LH; Barcus, M; Qi, L; McLean, J; Hariharan, P; Um, KS; Wu, S; Tabor, D; Shive, C; Smith, AM; Buia, SA; Undale, AH; Robinson, KL; Roche, N; Valentino, KM; Britton, A; Burges, R; Bradbury, D; Hambright, KW; Seleski, J; Korzeniewski, GE; Erickson, K; Marcus, Y; Tejada, J; Taherian, M; Lu, C; Basile, M; Mash, DC; Volpi, S; Struewing, JP; Temple, GF; Boyer, J; Colantuoni, D; Little, R; Koester, S; Carithers, LJ; Moore, HM; Guan, P; Compton, C; Sawyer, SJ; Demchok, JP; Vaught, JB; Rabiner, CA; Lockhart,;

Publication
Science

Abstract
Understanding the functional consequences of genetic variation, and how it affects complex human disease and quantitative traits, remains a critical challenge for biomedicine. We present an analysis of RNA sequencing data from 1641 samples across 43 tissues from 175 individuals, generated as part of the pilot phase of the Genotype-Tissue Expression (GTEx) project. We describe the landscape of gene expression across tissues, catalog thousands of tissue-specific and shared regulatory expression quantitative trait loci (eQTL) variants, describe complex network relationships, and identify signals from genome-wide association studies explained by eQTLs. These findings provide a systematic understanding of the cellular and biological consequences of human genetic variation and of the heterogeneity of such effects among a diverse set of human tissues.

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2015

Message from the chairs

Authors
Valente, A; Morais, R; Marques, L; Almeida, L;

Publication
Proceedings - 2015 IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2015

Abstract

2015

Guest Editorial ARC 2014

Authors
Goehringer, D; Santambrogio, MD; Cardoso, JMP; Bertels, K;

Publication
ACM Trans. Reconfigurable Technol. Syst.

Abstract

2015

A short note on type-inhabitation: Formula-trees vs. game semantics

Authors
Alves, S; Broda, S;

Publication
INFORMATION PROCESSING LETTERS

Abstract
This short note compares two different methods for exploring type-inhabitation in the simply typed lambda-calculus, highlighting their similarities.

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2015

SPECIAL ISSUE: Sustaining Resilience in Today's Demanding Environments

Authors
Azevedo, A; Almeida, A;

Publication
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING

Abstract

2015

A New Methodology for Solving the Unit Commitment in Insular Grids Including Uncertainty of Renewable Energies

Authors
Osorio, GJ; Lujano Rojas, JM; Matias, JCO; Catalao, JPS;

Publication
2015 IEEE 5TH INTERNATIONAL CONFERENCE ON POWER ENGINEERING, ENERGY AND ELECTRICAL DRIVES (POWERENG)

Abstract
Due to increasing integration of renewable generation into the electrical framework in last decades, the mathematical techniques required for the optimal day-ahead scheduling needs to be continuously improved, specifically for modeling the variability of these sources. In this paper, a method for producing a new solution for the stochastic unit commitment (UC) problem from the analysis of each scenario is developed. The methodology described in this paper can deal with a large number of scenario sets with a reasonable computational effort, by finding the common and feasible solutions for the scenario set under analysis.

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