National Autonomous University of Mexico

About: National Autonomous University of Mexico is a education organization based out in Mexico City, Distrito Federal, Mexico. It is known for research contribution in the topics: Population & Galaxy. The organization has 72868 authors who have published 127797 publications receiving 2285543 citations. The organization is also known as: UNAM & Universidad Nacional Autónoma de México.

What do we need to know about speciation

Abstract: Speciation has been a major focus of evolutionary biology research in recent years, with many important advances. However, some of the traditional organising principles of the subject area no longer provide a satisfactory framework, such as the classification of speciation mechanisms by geographical context into allopatric, parapatric and sympatry classes. Therefore, we have asked where speciation research should be directed in the coming years. Here, we present a distillation of questions about the mechanisms of speciation, the genetic basis of speciation and the relationship between speciation and diversity. Our list of topics is not exhaustive; rather we aim to promote discussion on research priorities and on the common themes that underlie disparate speciation processes.

Uniform Robust Exact Differentiator

Abstract: The differentiators based on the Super-Twisting Algorithm (STA) yield finite-time and theoretically exact convergence to the derivative of the input signal, whenever this derivative is Lipschitz. However, the convergence time grows unboundedly when the initial conditions of the differentiation error grow. In this technical note a Uniform Robust Exact Differentiator (URED) is introduced. The URED is based on a STA modification and includes high-degree terms providing finite-time, and exact convergence to the derivative of the input signal, with a convergence time that is bounded by some constant independent of the initial conditions of the differentiation error. Strong Lyapunov functions are used to prove the convergence of the URED.

Global Patterns and Predictions of Seafloor Biomass Using Random Forests

Abstract: A comprehensive seafloor biomass and abundance database has been constructed from 24 oceanographic institutions worldwide within the Census of Marine Life (CoML) field projects. The machine-learning algorithm, Random Forests, was employed to model and predict seafloor standing stocks from surface primary production, water-column integrated and export particulate organic matter (POM), seafloor relief, and bottom water properties. The predictive models explain 63% to 88% of stock variance among the major size groups. Individual and composite maps of predicted global seafloor biomass and abundance are generated for bacteria, meiofauna, macrofauna, and megafauna (invertebrates and fishes). Patterns of benthic standing stocks were positive functions of surface primary production and delivery of the particulate organic carbon (POC) flux to the seafloor. At a regional scale, the census maps illustrate that integrated biomass is highest at the poles, on continental margins associated with coastal upwelling and with broad zones associated with equatorial divergence. Lowest values are consistently encountered on the central abyssal plains of major ocean basins The shift of biomass dominance groups with depth is shown to be affected by the decrease in average body size rather than abundance, presumably due to decrease in quantity and quality of food supply. This biomass census and associated maps are vital components of mechanistic deep-sea food web models and global carbon cycling, and as such provide fundamental information that can be incorporated into evidence-based management.

RegulonDB version 7.0: transcriptional regulation of Escherichia coli K-12 integrated within genetic sensory response units (Gensor Units)

Abstract: RegulonDB (http://regulondbccgunammx/) is the primary reference database of the best-known regulatory network of any free-living organism, that of Escherichia coli K-12 The major conceptual change since 3 years ago is an expanded biological context so that transcriptional regulation is now part of a unit that initiates with the signal and continues with the signal transduction to the core of regulation, modifying expression of the affected target genes responsible for the response We call these genetic sensory response units, or Gensor Units We have initiated their high-level curation, with graphic maps and superreactions with links to other databases Additional connectivity uses expandable submaps RegulonDB has summaries for every transcription factor (TF) and TF-binding sites with internal symmetry Several DNA-binding motifs and their sizes have been redefined and relocated In addition to data from the literature, we have incorporated our own information on transcription start sites (TSSs) and transcriptional units (TUs), obtained by using high-throughput whole-genome sequencing technologies A new portable drawing tool for genomic features is also now available, as well as new ways to download the data, including web services, files for several relational database manager systems and text files including BioPAX format