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Liang Liu

Bio: Liang Liu is an academic researcher from Hong Kong Polytechnic University. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 56, co-authored 159 publications receiving 29271 citations. Previous affiliations of Liang Liu include University of Georgia & Shenzhen University.


Papers
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Journal ArticleDOI
TL;DR: The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly, and provides more output options than previously, including samples of ancestral states, site rates, site dN/dS rations, branch rates, and node dates.
Abstract: Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site d(N)/d(S) rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software.

18,718 citations

Journal ArticleDOI
Erich D. Jarvis1, Siavash Mirarab2, Andre J. Aberer3, Bo Li4, Bo Li5, Bo Li6, Peter Houde7, Cai Li6, Cai Li5, Simon Y. W. Ho8, Brant C. Faircloth9, Benoit Nabholz, Jason T. Howard1, Alexander Suh10, Claudia C. Weber10, Rute R. da Fonseca11, Jianwen Li, Fang Zhang Zhang, Hui Li, Long Zhou, Nitish Narula12, Nitish Narula7, Liang Liu13, Ganesh Ganapathy1, Bastien Boussau, Shamsuzzoha Bayzid2, Volodymyr Zavidovych1, Sankar Subramanian14, Toni Gabaldón15, Salvador Capella-Gutierrez, Jaime Huerta-Cepas, Bhanu Rekepalli16, Bhanu Rekepalli17, Kasper Munch18, Mikkel H. Schierup18, Bent E. K. Lindow11, Wesley C. Warren19, David A. Ray, Richard E. Green20, Michael William Bruford21, Xiangjiang Zhan21, Xiangjiang Zhan22, Andrew Dixon, Shengbin Li4, Ning Li23, Yinhua Huang23, Elizabeth P. Derryberry24, Elizabeth P. Derryberry25, Mads F. Bertelsen26, Frederick H. Sheldon25, Robb T. Brumfield25, Claudio V. Mello27, Claudio V. Mello28, Peter V. Lovell28, Morgan Wirthlin28, Maria Paula Cruz Schneider27, Francisco Prosdocimi27, José Alfredo Samaniego11, Amhed Missael Vargas Velazquez11, Alonzo Alfaro-Núñez11, Paula F. Campos11, Bent O. Petersen29, Thomas Sicheritz-Pontén29, An Pas, Thomas L. Bailey, R. Paul Scofield30, Michael Bunce31, David M. Lambert14, Qi Zhou, Polina L. Perelman32, Amy C. Driskell33, Beth Shapiro20, Zijun Xiong, Yongli Zeng, Shiping Liu, Zhenyu Li, Binghang Liu, Kui Wu, Jin Xiao, Xiong Yinqi, Quiemei Zheng, Yong Zhang, Huanming Yang, Jian Wang, Linnéa Smeds10, Frank E. Rheindt34, Michael J. Braun35, Jon Fjeldså11, Ludovic Orlando11, F. Keith Barker5, Knud A. Jønsson5, Warren E. Johnson33, Klaus-Peter Koepfli33, Stephen J. O'Brien36, David Haussler, Oliver A. Ryder, Carsten Rahbek5, Eske Willerslev11, Gary R. Graves33, Gary R. Graves5, Travis C. Glenn13, John E. McCormack37, Dave Burt38, Hans Ellegren10, Per Alström, Scott V. Edwards39, Alexandros Stamatakis3, David P. Mindell40, Joel Cracraft5, Edward L. Braun41, Tandy Warnow2, Tandy Warnow42, Wang Jun, M. Thomas P. Gilbert31, M. Thomas P. Gilbert5, Guojie Zhang11, Guojie Zhang6 
12 Dec 2014-Science
TL;DR: A genome-scale phylogenetic analysis of 48 species representing all orders of Neoaves recovered a highly resolved tree that confirms previously controversial sister or close relationships and identifies the first divergence in Neoaves, two groups the authors named Passerea and Columbea.
Abstract: To better determine the history of modern birds, we performed a genome-scale phylogenetic analysis of 48 species representing all orders of Neoaves using phylogenomic methods created to handle genome-scale data. We recovered a highly resolved tree that confirms previously controversial sister or close relationships. We identified the first divergence in Neoaves, two groups we named Passerea and Columbea, representing independent lineages of diverse and convergently evolved land and water bird species. Among Passerea, we infer the common ancestor of core landbirds to have been an apex predator and confirm independent gains of vocal learning. Among Columbea, we identify pigeons and flamingoes as belonging to sister clades. Even with whole genomes, some of the earliest branches in Neoaves proved challenging to resolve, which was best explained by massive protein-coding sequence convergence and high levels of incomplete lineage sorting that occurred during a rapid radiation after the Cretaceous-Paleogene mass extinction event about 66 million years ago.

1,624 citations

Journal ArticleDOI
TL;DR: In this paper, the authors considered a point-to-point wireless link over the narrowband flat-fading channel subject to time-varying co-channel interference and derived the optimal mode switching rule at the receiver to achieve various trade-offs between wireless information transfer and energy harvesting.
Abstract: Energy harvesting is a promising solution to prolong the operation of energy-constrained wireless networks. In particular, scavenging energy from ambient radio signals, namely wireless energy harvesting (WEH), has recently drawn significant attention. In this paper, we consider a point-to-point wireless link over the narrowband flat-fading channel subject to time-varying co-channel interference. It is assumed that the receiver has no fixed power supplies and thus needs to replenish energy opportunistically via WEH from the unintended interference and/or the intended signal sent by the transmitter. We further assume a single-antenna receiver that can only decode information or harvest energy at any time due to the practical circuit limitation. Therefore, it is important to investigate when the receiver should switch between the two modes of information decoding (ID) and energy harvesting (EH), based on the instantaneous channel and interference condition. In this paper, we derive the optimal mode switching rule at the receiver to achieve various trade-offs between wireless information transfer and energy harvesting. Specifically, we determine the minimum transmission outage probability for delay-limited information transfer and the maximum ergodic capacity for no-delay-limited information transfer versus the maximum average energy harvested at the receiver, which are characterized by the boundary of so-called "outage-energy" region and "rate-energy" region, respectively. Moreover, for the case when the channel state information (CSI) is known at the transmitter, we investigate the joint optimization of transmit power control, information and energy transfer scheduling, and the receiver's mode switching. The effects of circuit energy consumption at the receiver on the achievable rate-energy trade-offs are also characterized. Our results provide useful guidelines for the efficient design of emerging wireless communication systems powered by opportunistic WEH.

664 citations

Journal ArticleDOI
TL;DR: A Bayesian model for estimating species trees that accounts for the stochastic variation expected for gene trees from multiple unlinked loci sampled from a single species history after a coalescent process is analyzed.
Abstract: The vast majority of phylogenetic models focus on resolution of gene trees, despite the fact that phylogenies of species in which gene trees are embedded are of primary interest. We analyze a Bayesian model for estimating species trees that accounts for the stochastic variation expected for gene trees from multiple unlinked loci sampled from a single species history after a coalescent process. Application of the model to a 106-gene data set from yeast shows that the set of gene trees recovered by statistically acknowledging the shared but unknown species tree from which gene trees are sampled is much reduced compared with treating the history of each locus independently of an overarching species tree. The analysis also yields a concentrated posterior distribution of the yeast species tree whose mode is congruent with the concatenated gene tree but can do so with less than half the loci required by the concatenation method. Using simulations, we show that, with large numbers of loci, highly resolved species trees can be estimated under conditions in which concatenation of sequence data will positively mislead phylogeny, and when the proportion of gene trees matching the species tree is <10%. However, when gene tree/species tree congruence is high, species trees can be resolved with just two or three loci. These results make accessible an alternative paradigm for combining data in phylogenomics that focuses attention on the singularity of species histories and away from the idiosyncrasies and multiplicities of individual gene histories.

626 citations

Journal ArticleDOI
TL;DR: This paper considers a point-to-point wireless link over the flat-fading channel, where the receiver has no fixed power supplies and thus needs to replenish energy via WEH from the signals sent by the transmitter.
Abstract: Energy harvesting is a promising solution to prolong the operation time of energy-constrained wireless networks. In particular, scavenging energy from ambient radio signals, namely wireless energy harvesting (WEH), has recently drawn significant attention. In this paper, we consider a point-to-point wireless link over the flat-fading channel, where the receiver has no fixed power supplies and thus needs to replenish energy via WEH from the signals sent by the transmitter. We first consider a SISO (single-input single-output) system where the single-antenna receiver cannot decode information and harvest energy independently from the same signal received. Under this practical constraint, we propose a dynamic power splitting (DPS) scheme, where the received signal is split into two streams with adjustable power levels for information decoding and energy harvesting separately based on the instantaneous channel condition that is assumed to be known at the receiver. We derive the optimal power splitting rule at the receiver to achieve various trade-offs between the maximum ergodic capacity for information transfer and the maximum average harvested energy for power transfer, which are characterized by the boundary of a so-called "rate-energy (R-E)" region. Moreover, for the case when the channel state information is also known at the transmitter, we investigate the joint optimization of transmitter power control and receiver power splitting. The achievable R-E region by the proposed DPS scheme is also compared against that by the existing time switching scheme as well as a performance upper bound by ignoring the practical receiver constraint. Finally, we extend the result for optimal DPS to the SIMO (single-input multiple-output) system where the receiver is equipped with multiple antennas. In particular, we investigate a low-complexity power splitting scheme, namely antenna switching, which achieves the near-optimal rate-energy trade-offs as compared to the optimal DPS.

615 citations


Cited by
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Journal ArticleDOI
TL;DR: The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly, and provides more output options than previously, including samples of ancestral states, site rates, site dN/dS rations, branch rates, and node dates.
Abstract: Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site d(N)/d(S) rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software.

18,718 citations

Journal ArticleDOI
TL;DR: The software package Tracer is presented, for visualizing and analyzing the MCMC trace files generated through Bayesian phylogenetic inference, which provides kernel density estimation, multivariate visualization, demographic trajectory reconstruction, conditional posterior distribution summary, and more.
Abstract: Bayesian inference of phylogeny using Markov chain Monte Carlo (MCMC) plays a central role in understanding evolutionary history from molecular sequence data. Visualizing and analyzing the MCMC-generated samples from the posterior distribution is a key step in any non-trivial Bayesian inference. We present the software package Tracer (version 1.7) for visualizing and analyzing the MCMC trace files generated through Bayesian phylogenetic inference. Tracer provides kernel density estimation, multivariate visualization, demographic trajectory reconstruction, conditional posterior distribution summary, and more. Tracer is open-source and available at http://beast.community/tracer.

5,492 citations

01 Aug 2000
TL;DR: Assessment of medical technology in the context of commercialization with Bioentrepreneur course, which addresses many issues unique to biomedical products.
Abstract: BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

4,833 citations

Journal ArticleDOI
TL;DR: The current version of iTOL v4 introduces four new dataset types, together with numerous new features, and is the first tool which supports direct visualization of Qiime 2 trees and associated annotations.
Abstract: The Interactive Tree Of Life (https://itol.embl.de) is an online tool for the display, manipulation and annotation of phylogenetic and other trees. It is freely available and open to everyone. The current version introduces four new dataset types, together with numerous new features. Annotation options have been expanded and new control options added for many display elements. An interactive spreadsheet-like editor has been implemented, providing dataset creation and editing directly in the web interface. Font support has been rewritten with full support for UTF-8 character encoding throughout the user interface. Google Web Fonts are now fully supported in the tree text labels. iTOL v4 is the first tool which supports direct visualization of Qiime 2 trees and associated annotations. The user account system has been streamlined and expanded with new navigation options, and currently handles >700 000 trees from more than 40 000 individual users. Full batch access has been implemented allowing programmatic upload and export of trees and annotations.

4,233 citations