Algum membro da Nomenklatura científica tupiniquim se habilita debater o Dr. David Berlinski, filósofo e matemático, judeu, agnóstico, bon vivant residindo em Paris? Duvido! Mas se houver, seria um grande debate!
A System to Automatically Classify and Name Any Individual Genome-Sequenced Organism Independently of Current Biological Classification and Nomenclature
Haitham Marakeby equal contributor, Eman Badr equal contributor, Hanaa Torkey equal contributor, Yuhyun Song, Scotland Leman, Caroline L. Monteil, Lenwood S. Heath, Boris A. Vinatzer
Published: February 21, 2014DOI: 10.1371/journal.pone.0089142
A broadly accepted and stable biological classification system is a prerequisite for biological sciences. It provides the means to describe and communicate about life without ambiguity. Current biological classification and nomenclature use the species as the basic unit and require lengthy and laborious species descriptions before newly discovered organisms can be assigned to a species and be named. The current system is thus inadequate to classify and name the immense genetic diversity within species that is now being revealed by genome sequencing on a daily basis. To address this lack of a general intra-species classification and naming system adequate for today’s speed of discovery of new diversity, we propose a classification and naming system that is exclusively based on genome similarity and that is suitable for automatic assignment of codes to any genome-sequenced organism without requiring any phenotypic or phylogenetic analysis. We provide examples demonstrating that genome similarity-based codes largely align with current taxonomic groups at many different levels in bacteria, animals, humans, plants, and viruses. Importantly, the proposed approach is only slightly affected by the order of code assignment and can thus provide codes that reflect similarity between organisms and that do not need to be revised upon discovery of new diversity. We envision genome similarity-based codes to complement current biological nomenclature and to provide a universal means to communicate unambiguously about any genome-sequenced organism in fields as diverse as biodiversity research, infectious disease control, human and microbial forensics, animal breed and plant cultivar certification, and human ancestry research.
Como nós discutimos muitas vezes, a evolução é a teoria científica mais influente em áreas for a da ciência, pois a evolução porta uma mensagem que vai além da biologia. E qual é essa mensagem? Como Peter Singer sucintamente expressou, “A teoria de Darwin solapou os fundamentos de todo o modo de pensar do Ocidente sobre o lugar de nossa espécie no universo.” Isso pode soar abstrato, mas suas implicações não podiam ser mais reais. Esta metafísica subjacente da evolução permeia nossa cultura e, de clínicas de aborto às máquinas de guerra, tudo isso está impregnado em nosso modo de pensar. Transcende o espectro politico da direita e da esquerda procurando maneiras de substituir aqueles “certos direitos inalienáveis” com suas ideias de como deve ser tratada uma espécie que evoluiu por acaso. Na posição extrema, como este documentário explica, há uma “Guerra aos humanos”.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The fields of molecular biology and computer science have cooperated over recent years to create a synergy between the cybernetic and biosemiotic relationship found in cellular genomics to that of information and language found in computational systems. Biological information frequently manifests its "meaning" through instruction or actual production of formal bio-function. Such information is called Prescriptive Information (PI). PI programs organize and execute a prescribed set of choices. Closer examination of this term in cellular systems has led to a dichotomy in its definition suggesting both prescribed data and prescribed algorithms are constituents of PI. This paper looks at this dichotomy as expressed in both the genetic code and in the central dogma of protein synthesis. An example of a genetic algorithm is modeled after the ribosome, and an examination of the protein synthesis process is used to differentiate PI data from PI algorithms.
An extrapolation of the genetic complexity of organisms to earlier times suggests that life began before the Earth was formed. Life may have started from systems with single heritable elements that are functionally equivalent to a nucleotide. The genetic complexity, roughly measured by the number of non-redundant functional nucleotides, is expected to have grown exponentially due to several positive feedback factors: gene cooperation, duplication of genes with their subsequent specialization, and emergence of novel functional niches associated with existing genes. Linear regression of genetic complexity on a log scale extrapolated back to just one base pair suggests the time of the origin of life 9.7 billion years ago. This cosmic time scale for the evolution of life has important consequences: life took ca. 5 billion years to reach the complexity of bacteria; the environments in which life originated and evolved to the prokaryote stage may have been quite different from those envisaged on Earth; there was no intelligent life in our universe prior to the origin of Earth, thus Earth could not have been deliberately seeded with life by intelligent aliens; Earth was seeded by panspermia; experimental replication of the origin of life from scratch may have to emulate many cumulative rare events; and the Drake equation for guesstimating the number of civilizations in the universe is likely wrong, as intelligent life has just begun appearing in our universe. Evolution of advanced organisms has accelerated via development of additional information-processing systems: epigenetic memory, primitive mind, multicellular brain, language, books, computers, and Internet. As a result the doubling time of complexity has reached ca. 20 years. Finally, we discuss the issue of the predicted technological singularity and give a biosemiotics perspective on the increase of complexity.
Comments:26 pages, 3 figures
Subjects:General Physics (physics.gen-ph)
Cite as:arXiv:1304.3381 [physics.gen-ph]
(or arXiv:1304.3381v1 [physics.gen-ph] for this version)
We confront the hot big bang for the beginning of the universe with an equivalent picture of a slow freeze - a very cold and slowly evolving universe. In the slow freeze picture the masses of elementary particles increase and the gravitational constant decreases with cosmic time, while the Newtonian attraction remains unchanged. The slow freeze and hot big bang pictures both describe the same observations or physical reality. We present a simple three-parameter "crossover model" without a "big bang singularity". In the infinite past space-time is flat. Our model is compatible with all present observations, describing the generation of primordial density fluctuations during inflation as well as the present transition to a dark energy dominated universe.
Comments:9 pages, 1 figure
Subjects:Cosmology and Extragalactic Astrophysics (astro-ph.CO); General Relativity and Quantum Cosmology (gr-qc); High Energy Physics - Theory (hep-th)
Cite as:arXiv:1401.5313 [astro-ph.CO]
(or arXiv:1401.5313v1 [astro-ph.CO] for this version)
Por que sou ‘pós-darwinista’? Porque já fui evolucionista de carteirinha. Hoje, sou cético da teoria macroevolutiva como verdade científica. Contudo, meu ceticismo ao ‘dogma central’ darwinista não é baseado em relatos da criação de textos sagrados. Foi a séria e conflituosa consideração do debate que ocorre intramuros e nas publicações científicas há muitos anos sobre a insuficiência epistêmica da teoria geral da evolução. Eu fui ateu marxista-leninista. Hoje, não tenho mais fé cega no ateísmo. Não creio mais na interpretação literal dos dogmas de Darwin aceitos ‘a priori’ e defendidos ideologicamente com unhas e dentes pela Nomenklatura científica. A Ciência me deu esta convicção. Aprendi na universidade: quando uma teoria científica não é apoiada pelas evidências, ela deve ser revista ou simplesmente descartada. Sou pós-darwinista me antecipando à iminente e eminente ruptura paradigmática em biologia evolutiva. Chegou a hora de dizer adeus a Darwin. Mestre em História da Ciência – PUC-SP. CV Plataforma Lattes: http://lattes.cnpq.br/6602620537249723