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The proteome landscape of the kingdoms of life 期刊论文
NATURE, 2020
作者:  Arzi, Anat;  Rozenkrantz, Liron;  Gorodisky, Lior;  Rozenkrantz, Danit;  Holtzman, Yael;  Ravia, Aharon;  Bekinschtein, Tristan A.;  Galperin, Tatyana;  Krimchansky, Ben-Zion;  Cohen, Gal;  Oksamitni, Anna;  Aidinoff, Elena;  Sacher, Yaron;  Sobel, Noam
收藏  |  浏览/下载:14/0  |  提交时间:2020/07/03

Proteins carry out the vast majority of functions in all biological domains, but for technological reasons their large-scale investigation has lagged behind the study of genomes. Since the first essentially complete eukaryotic proteome was reported(1), advances in mass-spectrometry-based proteomics(2)have enabled increasingly comprehensive identification and quantification of the human proteome(3-6). However, there have been few comparisons across species(7,8), in stark contrast with genomics initiatives(9). Here we use an advanced proteomics workflow-in which the peptide separation step is performed by a microstructured and extremely reproducible chromatographic system-for the in-depth study of 100 taxonomically diverse organisms. With two million peptide and 340,000 stringent protein identifications obtained in a standardized manner, we double the number of proteins with solid experimental evidence known to the scientific community. The data also provide a large-scale case study for sequence-based machine learning, as we demonstrate by experimentally confirming the predicted properties of peptides fromBacteroides uniformis. Our results offer a comparative view of the functional organization of organisms across the entire evolutionary range. A remarkably high fraction of the total proteome mass in all kingdoms is dedicated to protein homeostasis and folding, highlighting the biological challenge of maintaining protein structure in all branches of life. Likewise, a universally high fraction is involved in supplying energy resources, although these pathways range from photosynthesis through iron sulfur metabolism to carbohydrate metabolism. Generally, however, proteins and proteomes are remarkably diverse between organisms, and they can readily be explored and functionally compared at www.proteomesoflife.org.


  
Negative emissions and international climate goals-learning from and about mitigation scenarios 期刊论文
CLIMATIC CHANGE, 2019
作者:  Hilaire, Jerome;  Minx, Jan C.;  Callaghan, Max W.;  Edmonds, Jae;  Luderer, Gunnar;  Nemet, Gregory F.;  Rogelj, Joeri;  Zamora, Maria del Mar
收藏  |  浏览/下载:12/0  |  提交时间:2019/11/27
Negative emission  Carbon dioxide removal  Systematic evidence synthesis  Integrated assessment model  1  5 degrees C  2 degrees C  
Heterogeneities in energy technological learning: Evidence from the US electricity industry 期刊论文
ENERGY POLICY, 2019, 132: 1034-1049
作者:  Shittu, Ekundayo;  Kamdem, Bruno G.;  Weigelt, Carmen
收藏  |  浏览/下载:12/0  |  提交时间:2019/11/27
Technological learning  Policy  Knowledge acquisition  Electricity industry  
How can Big Data and machine learning benefit environment and water management: a survey of methods, applications, and future directions 期刊论文
ENVIRONMENTAL RESEARCH LETTERS, 2019, 14 (7)
作者:  Sun, Alexander Y.;  Scanlon, Bridget R.
收藏  |  浏览/下载:8/0  |  提交时间:2019/11/27
machine learning  deep learning  predictive analytics  artificial intelligence  environmental management  big Data  remote sensing  
Subsidizing renewables as part of taking leadership in international climate policy: The German case 期刊论文
ENERGY POLICY, 2019, 129: 765-773
作者:  Buchholz, Wolfgang;  Dippl, Lisa;  Eichenseer, Michael
收藏  |  浏览/下载:5/0  |  提交时间:2019/11/26
Leadership  Climate change  Solar photovoltaic  Subsidies  Feed-intariffs  Ambition  
From fossil fuels to renewables: An analysis of long-term scenarios considering technological learning 期刊论文
ENERGY POLICY, 2019, 127: 134-146
作者:  Handayani, Kamia;  Krozer, Yoram;  Filatova, Tatiana
收藏  |  浏览/下载:14/0  |  提交时间:2019/11/26
Renewable energy  Technological learning  LEAP  Climate change mitigation  Indonesia  
Rare breakthroughs vs. incremental development in R&D strategy for an early-stage energy technology 期刊论文
ENERGY POLICY, 2018, 123: 711-721
作者:  Fertig, Emily
收藏  |  浏览/下载:5/0  |  提交时间:2019/04/09
Real options  R&D  Stochastic dynamic programming  Carbon capture and sequestration  Managerial flexibility  Endogenous technological change  
Interactions between social learning and technological learning in electric vehicle futures 期刊论文
ENVIRONMENTAL RESEARCH LETTERS, 2018, 13 (12)
作者:  Edelenbosch, O. Y.;  McCollum, David L.;  Pettifor, Hazel;  Wilson, Charlie;  van Vuuren, Detlef P.
收藏  |  浏览/下载:9/0  |  提交时间:2019/04/09
transport modelling  vehicle choice  social influence  technological learning  
Knowledge flow in low-carbon technology transfer: A case of India's wind power industry 期刊论文
ENERGY POLICY, 2018, 123: 104-116
作者:  Hayashi, Daisuke
收藏  |  浏览/下载:1/0  |  提交时间:2019/04/09
Technology transfer  Technological capabilities  Knowledge Innovation  Wind power  India  
Evaluating the causes of cost reduction in photovoltaic modules 期刊论文
ENERGY POLICY, 2018, 123: 700-710
作者:  Kavlak, Goksin;  McNerney, James;  Trancik, Jessika E.
收藏  |  浏览/下载:5/0  |  提交时间:2019/04/09
Photovoltaics (PV)  Solar energy  PV modules  Cost model  Technological change