Species to genera: phylogenetic inference in the Hawaiian Drosophilidae

2002 ◽  
pp. 17-30 ◽  
Author(s):  
Patrick M. O’Grady
Keyword(s):  
Phylogenetic Inference

Near-memory Acceleration for Scalable Phylogenetic Inference

2020 ◽  
Author(s):  
Nikolaos Alachiotis ◽  
Panagiotis Skrimponis ◽  
Manolis Pissadakis ◽  
Sundeep Rangan ◽  
Dionisios Pnevmatikatos
Keyword(s):  
Phylogenetic Inference

scholarly journals The complete chloroplast genome of Atractylodes japonica Koidz. ex Kitam. and its phylogenetic inference

2021 ◽  
Vol 6 (7) ◽  
pp. 2038-2040
Author(s):  
Mengmeng Shi ◽  
Hongbo Xie ◽  
Chunying Zhao ◽  
Linchun Shi ◽  
Jinxin Liu ◽  
...  
Keyword(s):  
Chloroplast Genome ◽  
Phylogenetic Inference ◽  
Complete Chloroplast Genome ◽  
Atractylodes Japonica

Machine learning for rediscovering revolutionary ideas of the past

2021 ◽  
pp. 105971232098304
Author(s):  
R Alexander Bentley ◽  
Joshua Borycz ◽  
Simon Carrignon ◽  
Damian J Ruck ◽  
Michael J O’Brien
Keyword(s):  
Language Processing ◽  
Scientific Progress ◽  
Phylogenetic Inference ◽  
The Past ◽  
New Methods ◽  
Inherent Nature ◽  
Social Learning Processes ◽  
High Level ◽  
Scientific Ideas ◽  
Revolutionary Science

The explosion of online knowledge has made knowledge, paradoxically, difficult to find. A web or journal search might retrieve thousands of articles, ranked in a manner that is biased by, for example, popularity or eigenvalue centrality rather than by informed relevance to the complex query. With hundreds of thousands of articles published each year, the dense, tangled thicket of knowledge grows even more entwined. Although natural language processing and new methods of generating knowledge graphs can extract increasingly high-level interpretations from research articles, the results are inevitably biased toward recent, popular, and/or prestigious sources. This is a result of the inherent nature of human social-learning processes. To preserve and even rediscover lost scientific ideas, we employ the theory that scientific progress is punctuated by means of inspired, revolutionary ideas at the origin of new paradigms. Using a brief case example, we suggest how phylogenetic inference might be used to rediscover potentially useful lost discoveries, as a way in which machines could help drive revolutionary science.

Integrative taxonomic and geographic variation analyses in Cyrtodactylus aequalis (Squamata: Gekkonidae) from southern Myanmar (Burma): one species, two different stories

2020 ◽  
Vol 66 (3-4) ◽  
pp. 151-179
Author(s):  
L. Lee Grismer ◽  
L. Wood Perry ◽  
Marta S. Grismer ◽  
Evan S.H. Quah ◽  
Myint Kyaw Thura ◽  
...  
Keyword(s):  
Geographic Variation ◽  
Evolutionary History ◽  
Phylogenetic Inference ◽  
Morphological Characters ◽  
Molecular Data ◽  
Biodiversity Crisis ◽  
Allopatric Populations ◽  
Compelling Argument ◽  
Historical Accuracy ◽  
Molecular Phylogenetic

The historical accuracy of building taxonomies is improved when they are based on phylogenetic inference (i.e., the resultant classifications are less apt to misrepresent evolutionary history). In fact, taxonomies inferred from statistically significant diagnostic morphological characters in the absence of phylogenetic considerations, can contain non-monophyletic lineages. This is especially true at the species level where small amounts of gene flow may not preclude the evolution of localized adaptions in different geographic areas while underpinning the paraphyletic nature of each population with respect to the other. We illustrate this point by examining genetic and morphological variation among three putatively allopatric populations of the granite-dwelling Bent-toed Gecko Cyrtodactylus aequalis from hilly regions in southeastern Myanmar. In the absence of molecular phylogenetic inference, a compelling argument for three morphologically diagnosable species could be marshaled. However, when basing the morphological analyses of geographic variation on a molecular phylogeny, there is a more compelling argument that only one species should be recognized. We are cognizant of the fact however, that when dealing with rare species or specimens for which no molecular data are possible, judicious morphological analyses are the only option—and the desired option given the current worldwide biodiversity crisis.

scholarly journals Markov-Modulated Continuous-Time Markov Chains to Identify Site- and Branch-Specific Evolutionary Variation in BEAST

2020 ◽  
Vol 70 (1) ◽  
pp. 181-189
Author(s):  
Guy Baele ◽  
Mandev S Gill ◽  
Paul Bastide ◽  
Philippe Lemey ◽  
Marc A Suchard
Keyword(s):  
High Performance ◽  
Markov Models ◽  
Marginal Likelihood ◽  
Likelihood Estimation ◽  
Phylogenetic Inference ◽  
Time Variability ◽  
Substitution Process ◽  
Wide Range ◽  
Markov Modulated ◽  
Over Time

Abstract Markov models of character substitution on phylogenies form the foundation of phylogenetic inference frameworks. Early models made the simplifying assumption that the substitution process is homogeneous over time and across sites in the molecular sequence alignment. While standard practice adopts extensions that accommodate heterogeneity of substitution rates across sites, heterogeneity in the process over time in a site-specific manner remains frequently overlooked. This is problematic, as evolutionary processes that act at the molecular level are highly variable, subjecting different sites to different selective constraints over time, impacting their substitution behavior. We propose incorporating time variability through Markov-modulated models (MMMs), which extend covarion-like models and allow the substitution process (including relative character exchange rates as well as the overall substitution rate) at individual sites to vary across lineages. We implement a general MMM framework in BEAST, a popular Bayesian phylogenetic inference software package, allowing researchers to compose a wide range of MMMs through flexible XML specification. Using examples from bacterial, viral, and plastid genome evolution, we show that MMMs impact phylogenetic tree estimation and can substantially improve model fit compared to standard substitution models. Through simulations, we show that marginal likelihood estimation accurately identifies the generative model and does not systematically prefer the more parameter-rich MMMs. To mitigate the increased computational demands associated with MMMs, our implementation exploits recent developments in BEAGLE, a high-performance computational library for phylogenetic inference. [Bayesian inference; BEAGLE; BEAST; covarion, heterotachy; Markov-modulated models; phylogenetics.]

scholarly journals Support for linguistic macrofamilies from weighted sequence alignment

2015 ◽  
Vol 112 (41) ◽  
pp. 12752-12757 ◽  
Author(s):  
Gerhard Jäger
Keyword(s):  
Historical Linguistics ◽  
Large Body ◽  
Phylogenetic Inference ◽  
Controversial Issues ◽  
Phonetic Transcription ◽  
Lexical Change ◽  
Statistical Support ◽  
Core Vocabulary ◽  
Computational Phylogenetics ◽  
String Alignment

Computational phylogenetics is in the process of revolutionizing historical linguistics. Recent applications have shed new light on controversial issues, such as the location and time depth of language families and the dynamics of their spread. So far, these approaches have been limited to single-language families because they rely on a large body of expert cognacy judgments or grammatical classifications, which is currently unavailable for most language families. The present study pursues a different approach. Starting from raw phonetic transcription of core vocabulary items from very diverse languages, it applies weighted string alignment to track both phonetic and lexical change. Applied to a collection of ∼1,000 Eurasian languages and dialects, this method, combined with phylogenetic inference, leads to a classification in excellent agreement with established findings of historical linguistics. Furthermore, it provides strong statistical support for several putative macrofamilies contested in current historical linguistics. In particular, there is a solid signal for the Nostratic/Eurasiatic macrofamily.

scholarly journals Indel Reliability in Indel-Based Phylogenetic Inference

2014 ◽  
Vol 6 (12) ◽  
pp. 3199-3209 ◽  
Author(s):  
Haim Ashkenazy ◽  
Ofir Cohen ◽  
Tal Pupko ◽  
Dorothée Huchon
Keyword(s):  
Phylogenetic Inference

scholarly journals Single-cell mutation identification via phylogenetic inference

2018 ◽  
Vol 9 (1) ◽  
Author(s):  
Jochen Singer ◽  
Jack Kuipers ◽  
Katharina Jahn ◽  
Niko Beerenwinkel
Keyword(s):  
Single Cell ◽  
Phylogenetic Inference ◽  
Cell Mutation ◽  
Mutation Identification
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