Institution
Aalto University
Education•Espoo, Finland•
About: Aalto University is a education organization based out in Espoo, Finland. It is known for research contribution in the topics: Population & Carbon nanotube. The organization has 9969 authors who have published 32648 publications receiving 829626 citations. The organization is also known as: TKK & Aalto-korkeakoulu.
Topics: Population, Carbon nanotube, Cellulose, Graphene, Thin film
Papers published on a yearly basis
Papers
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TL;DR: This manuscript aims at making recommendations for a number of important data acquisition and data analysis steps and suggests details that should be specified in manuscripts reporting MEG studies, in order to facilitate interpretation and reproduction of the results.
603 citations
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TL;DR: This work presents CSI:FingerID, which combines fragmentation tree computation and machine learning for searching molecular structure databases using tandem MS data of small molecules, and is shown to improve on the competing methods for computational metabolite identification by a considerable margin.
Abstract: Metabolites provide a direct functional signature of cellular state. Untargeted metabolomics experiments usually rely on tandem MS to identify the thousands of compounds in a biological sample. Today, the vast majority of metabolites remain unknown. We present a method for searching molecular structure databases using tandem MS data of small molecules. Our method computes a fragmentation tree that best explains the fragmentation spectrum of an unknown molecule. We use the fragmentation tree to predict the molecular structure fingerprint of the unknown compound using machine learning. This fingerprint is then used to search a molecular structure database such as PubChem. Our method is shown to improve on the competing methods for computational metabolite identification by a considerable margin.
598 citations
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TL;DR: The results demonstrate the importance of understanding host–microbe interactions to gain better insight into human health and demonstrate the influence of host genetics on microbial species, pathways and gene ontology categories on the basis of metagenomic sequencing in 1,514 subjects.
Abstract: The gut microbiome is affected by multiple factors, including genetics. In this study, we assessed the influence of host genetics on microbial species, pathways and gene ontology categories, on the basis of metagenomic sequencing in 1,514 subjects. In a genome-wide analysis, we identified associations of 9 loci with microbial taxonomies and 33 loci with microbial pathways and gene ontology terms at P < 5 × 10-8. Additionally, in a targeted analysis of regions involved in complex diseases, innate and adaptive immunity, or food preferences, 32 loci were identified at the suggestive level of P < 5 × 10-6. Most of our reported associations are new, including genome-wide significance for the C-type lectin molecules CLEC4F-CD207 at 2p13.3 and CLEC4A-FAM90A1 at 12p13. We also identified association of a functional LCT SNP with the Bifidobacterium genus (P = 3.45 × 10-8) and provide evidence of a gene-diet interaction in the regulation of Bifidobacterium abundance. Our results demonstrate the importance of understanding host-microbe interactions to gain better insight into human health.
597 citations
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TL;DR: A comprehensive review on bilevel optimization from the basic principles to solution strategies is provided in this paper, where a number of potential application problems are also discussed and an automated text-analysis of an extended list of papers has been performed.
Abstract: Bilevel optimization is defined as a mathematical program, where an optimization problem contains another optimization problem as a constraint. These problems have received significant attention from the mathematical programming community. Only limited work exists on bilevel problems using evolutionary computation techniques; however, recently there has been an increasing interest due to the proliferation of practical applications and the potential of evolutionary algorithms in tackling these problems. This paper provides a comprehensive review on bilevel optimization from the basic principles to solution strategies; both classical and evolutionary. A number of potential application problems are also discussed. To offer the readers insights on the prominent developments in the field of bilevel optimization, we have performed an automated text-analysis of an extended list of papers published on bilevel optimization to date. This paper should motivate evolutionary computation researchers to pay more attention to this practical yet challenging area.
588 citations
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TL;DR: A systematic literature review on how agile methods and lean software development has been adopted at scale, focusing on reported challenges and success factors in the transformation, identified 35 reported challenges grouped into nine categories, and 29 success factors, grouped into eleven categories.
572 citations
Authors
Showing all 10135 results
Name | H-index | Papers | Citations |
---|---|---|---|
John B. Goodenough | 151 | 1064 | 113741 |
Ashok Kumar | 151 | 5654 | 164086 |
Anne Lähteenmäki | 116 | 485 | 81977 |
Kalyanmoy Deb | 112 | 713 | 122802 |
Riitta Hari | 111 | 491 | 43873 |
Robin I. M. Dunbar | 111 | 586 | 47498 |
Andreas Richter | 110 | 769 | 48262 |
Mika Sillanpää | 96 | 1019 | 44260 |
Muhammad Farooq | 92 | 1341 | 37533 |
Ivo Babuška | 90 | 376 | 41465 |
Merja Penttilä | 87 | 303 | 22351 |
Andries Meijerink | 87 | 426 | 29335 |
T. Poutanen | 86 | 120 | 33158 |
Sajal K. Das | 85 | 1124 | 29785 |
Kalle Lyytinen | 84 | 426 | 27708 |