Binomial nomenclature

In taxonomy, binomial nomenclature ("two-term naming system"), also called nomenclature ("two-name naming system") or binary nomenclature, is a formal system of naming species of living things by giving each a name composed of two parts, both of which use Latin grammatical forms, although they can be based on words from other languages. Such a name is called a binomial name (which may be shortened to just "binomial"), a binomen, name, or a scientific name; more informally it is also historically called a Latin name. The first part of the name – the generic name – identifies the genus to which the species belongs, whereas the second part – the specific name or specific epithet – distinguishes the species within the genus. For example, modern humans belong to the genus Homo and within this genus to the species Homo sapiens. Tyrannosaurus rex is likely the most widely known binomial. The formal introduction of this

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Taxonomy (biology)

In biology, taxonomy () is the scientific study of naming, defining (circumscribing) and classifying groups of biological organisms based on shared characteristics. Organisms are grouped into taxa (s

Species

In biology, a species (: species) is often defined as the largest group of organisms in which any two individuals of the appropriate sexes or mating types can produce fertile offspring, typically by

Genus

Genus (ˈdʒiːnəs : genera ˈdʒɛnərə) is a taxonomic rank used in the biological classification of living and fossil organisms as well as viruses. In the hierarchy of biological classification, genus com

A community-based transcriptomics classification and nomenclature of neocortical cell types

Parviz Ghaderi, Jean Rossier

To understand the function of cortical circuits, it is necessary to catalog their cellular diversity. Past attempts to do so using anatomical, physiological or molecular features of cortical cells have not resulted in a unified taxonomy of neuronal or glial cell types, partly due to limited data. Single-cell transcriptomics is enabling, for the first time, systematic high-throughput measurements of cortical cells and generation of datasets that hold the promise of being complete, accurate and permanent. Statistical analyses of these data reveal clusters that often correspond to cell types previously defined by morphological or physiological criteria and that appear conserved across cortical areas and species. To capitalize on these new methods, we propose the adoption of a transcriptome-based taxonomy of cell types for mammalian neocortex. This classification should be hierarchical and use a standardized nomenclature. It should be based on a probabilistic definition of a cell type and incorporate data from different approaches, developmental stages and species. A community-based classification and data aggregation model, such as a knowledge graph, could provide a common foundation for the study of cortical circuits. This community-based classification, nomenclature and data aggregation could serve as an example for cell type atlases in other parts of the body.

NATURE PUBLISHING GROUP2020

Classification of degenerative parkinsonism subtypes by support-vector-machine analysis and striatal I-123-FP-CIT indices

Maria Giulia Preti, Dimitri Nestor Alice Van De Ville

ObjectivesTo provide an automated classification method for degenerative parkinsonian syndromes (PS) based on semiquantitative I-123-FP-CIT SPECT striatal indices and support-vector-machine (SVM) analysis.Methods(123)I-FP-CIT SPECT was performed at a single-center level on 370 individuals with PS, including 280 patients with Parkinson's disease (PD), 21 with multiple system atrophy-parkinsonian type (MSA-P), 41 with progressive supranuclear palsy (PSP) and 28 with corticobasal syndrome (CBS) (mean age 70.3years, 47% female, mean disease duration at scan 1.4year), as well as 208 age- and gender-matched control subjects. Striatal volumes-of-interest (VOIs) uptake, VOIs asymmetry indices (AIs) and caudate/putamen (C/P) ratio were used as input for SVM individual classification using fivefold cross-validation.ResultsUnivariate analyses showed significantly lower VOIs uptake, higher striatal AI and C/P ratio for each PS in comparison to controls (all p70% accuracy. Overall, striatal AI and C/P ratio on the more affected side had the highest weighting factors.ConclusionSemiquantitative I-123-FP-CIT SPECT striatal evaluation combined with SVM represents a promising approach to disentangle PD from non-degenerative conditions and from atypical PS at the early stage.

Springer2019

New insights into the classification and nomenclature of cortical GABAergic interneurons

Ruth Benavides Piccione, Sean Lewis Hill, Zoltan Kisvarday, Henry Markram, Jean Rossier, Yun Wang

A systematic classification and accepted nomenclature of neuron types is much needed but is currently lacking. This article describes a possible taxononnical solution for classifying GABAergic interneurons of the cerebral cortex based on a novel, web-based interactive system that allows experts to classify neurons with pre-determined criteria. Using Bayesian analysis and clustering algorithms on the resulting data, we investigated the suitability of several anatomical terms and neuron names for cortical GABAergic interneurons. Moreover, we show that supervised classification models could automatically categorize interneurons in agreement with experts' assignments. These results demonstrate a practical and objective approach to the naming, characterization and classification of neurons based on community consensus.

Nature Publishing Group2013

MSE-211: Organic chemistry

This course provides a basic foundation in organic chemistry and polymer chemistry, including chemical nomenclature of organic compounds and polymers, an understanding of chemical structures, chemical reaction mechanisms, as well as methods of organic and polymer synthesis.

CH-112: Organic chemistry

L'objectif de ce cours est de fournir les connaissances et le moyen de comprendre, au niveau moléculaire, le fonctionnement des réactions chimiques organiques. Pendant le cours, l'étudiant réfléchira et résoudra de nouveaux problèmes.

CH-120: Advanced general chemistry II

Acquisition des notions fondamentales liées à la réactivité des molécules organiques, identification de la structure de petites molécules organiques au moyen des techniques de spectrométrie de masse, spectroscopie infra-rouge et résonance magnétique nucléaire.