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How Not to Be Wrong: The Power of Mathematical Thinking eBook: Jordan Ellenberg: Amazon.ca: Kindle Store

How Not to Be Wrong: The Power of Mathematical Thinking eBook: Jordan Ellenberg: Amazon.ca: Kindle Store

Source: www.amazon.ca

MATH and STATS in real life….   why it matters!

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Samba virus: a novel mimivirus from a giant rain forest, the Brazilian Amazon

The identification of novel giant viruses from the nucleocytoplasmic large DNA viruses group and their virophages has increased in the last decade and has helped to shed light on viral evolution. This study describe the discovery, isolation and characterization of Samba virus (SMBV), a novel giant virus belonging to the Mimivirus genus, which was isolated from the Negro River in the Brazilian Amazon. We also report the isolation of an SMBV-associated virophage named Rio Negro (RNV), which is the first Mimivirus virophage to be isolated in the Americas.

Source: www.virologyj.com

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Virology Journal | Abstract | Mutations within the conserved NS1 nuclear export signal lead to inhibition of influenza A virus replication

The influenza A virus NS1 protein is a virulence factor and an antagonist of host cell innate immune responses. During virus infection NS1 protein has several functions both in the nucleus and in the cytoplasm and its intracellular localization is regulated by one or two nuclear localization signals (NLS) and a nuclear export signal (NES).

Source: www.virologyj.com

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SimFlu: A simulation tool for predicting the variation pattern of influenza A virus.

Since the first pandemic outbreak of avian influenza A virus (H5N1 subtype) in 1997, the National Center for Biotechnology Information (NCBI) has provided a large number of influenza virus sequences with well-organized annotations. Using the time-series sequences of influenza A viruses, we developed a simulation tool for influenza virus, named SimFlu, to predict possible future variants of influenza viruses. SimFlu can create variants from a seed nucleotide sequence of influenza A virus using the codon variation parameters included in the SimFlu package. The SimFlu library provides pre-calculated codon variation parameters for the H1N1, H3N2, and H5N1 subtypes of influenza A virus isolated from 2000 to 2011, allowing the users to simulate their own nucleotide sequences by selecting their preferred parameter options. SimFlu supports three operating systems – Windows, Linux, and Mac OS X. SimFlu is publicly available at http://lcbb.snu.ac.kr/simflu.

Source: www.ncbi.nlm.nih.gov

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CDC Media Statement on Newly Discovered Smallpox Samples

On July 1, 2014, the National Institutes of Health (NIH) notified the appropriate regulatory agency, the Division of Select Agents and Toxins (DSAT) of the Centers for Disease Control and Prevention (CDC), that employees discovered vials labeled ”variola,” commonly known as smallpox, in an unused portion of a storage room in a Food and Drug Administration (FDA) laboratory located on the NIH Bethesda campus.

Source: www.cdc.gov

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Evolution and Ecology of Influenza A Viruses.

Wild aquatic bird populations have long been considered the natural reservoir for influenza A viruses with virus transmission from these birds seeding other avian and mammalian hosts. While most evidence still supports this dogma, recent studies in bats have suggested other reservoir species may also exist. Extensive surveillance studies coupled with an enhanced awareness in response to H5N1 and pandemic 2009 H1N1 outbreaks is also revealing a growing list of animals susceptible to infection with influenza A viruses. Although in a relatively stable host-pathogen interaction in aquatic birds, antigenic, and genetic evolution of influenza A viruses often accompanies interspecies transmission as the virus adapts to a new host. The evolutionary changes in the new hosts result from a number of processes including mutation, reassortment, and recombination. Depending on host and virus these changes can be accompanied by disease outbreaks impacting wildlife, veterinary, and public health.

 

Source: www.ncbi.nlm.nih.gov

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Simple chained guide trees give high-quality protein multiple sequence alignments Boyce K, Sievers F, Higgins DG

Guide trees are used to decide the order of sequence alignment in the progressive multiple sequence alignment heuristic. These guide trees are often the limiting factor in making large alignments, and considerable effort has been expended over the years in making these quickly or accurately. In this article we show that, at least for protein families with large numbers of sequences that can be benchmarked with known structures, simple chained guide trees give the most accurate alignments. These also happen to be the fastest and simplest guide trees to construct, computationally. Such guide trees have a striking effect on the accuracy of alignments produced by some of the most widely used alignment packages. There is a marked increase in accuracy and a marked decrease in computational time, once the number of sequences goes much above a few hundred. This is true, even if the order of sequences in the guide tree is random.

 

Source: www.ncbi.nlm.nih.gov