J legend biography 3ds max 2017

  • Jay chou young
  • An efficient targeted nuclease strategy for high-resolution mapping of DNA binding sites

    Abstract

    We describe Cleavage Under Targets and Release Using Nuclease (CUT&RUN), a chromatin profiling strategy in which antibody-targeted controlled cleavage by micrococcal nuclease releases specific protein-DNA complexes into the supernatant for paired-end DNA sequencing. Unlike Chromatin Immunoprecipitation (ChIP), which fragments and solubilizes total chromatin, CUT&RUN is performed in situ, allowing for both quantitative high-resolution chromatin mapping and probing of the local chromatin environment. When applied to yeast and human nuclei, CUT&RUN yielded precise transcription factor profiles while avoiding crosslinking and solubilization issues. CUT&RUN is simple to perform and is inherently robust, with extremely low backgrounds requiring only ~1/10th the sequencing depth as ChIP, making CUT&RUN especially cost-effective for transcription factor and chromatin profiling. When used in conjunction with native ChIP-seq and applied to human CTCF, CUT&RUN mapped directional long range contact sites at high resolution. We conclude that in situ mapping of protein-DNA interactions by CUT&RUN is an attractive alternative to ChIP-seq.

    DOI:http://dx.doi.org/10.7554/eLife.21856.001

    Research Organism:S. cerevisiae, Human

    eLife digest

    The DNA in a person’s skin cell will contain the same genes as the DNA in their muscle or brain cells. However, these cells have different identities because different genes are active in skin, muscle and brain cells. Proteins called transcription factors dictate the patterns of gene activation in the different kinds of cells by binding to DNA and switching nearby genes on or off. Transcription factors interact with other proteins such as histones that help to package DNA into a structure known as chromatin. Together, transcription factors, histones and other chromatin-associated proteins determine whether or no

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  • Highly accurate protein structure prediction with AlphaFold

    Main

    The development of computational methods to predict three-dimensional (3D) protein structures from the protein sequence has proceeded along two complementary paths that focus on either the physical interactions or the evolutionary history. The physical interaction programme heavily integrates our understanding of molecular driving forces into either thermodynamic or kinetic simulation of protein physics or statistical approximations thereof. Although theoretically very appealing, this approach has proved highly challenging for even moderate-sized proteins due to the computational intractability of molecular simulation, the context dependence of protein stability and the difficulty of producing sufficiently accurate models of protein physics. The evolutionary programme has provided an alternative in recent years, in which the constraints on protein structure are derived from bioinformatics analysis of the evolutionary history of proteins, homology to solved structures and pairwise evolutionary correlations. This bioinformatics approach has benefited greatly from the steady growth of experimental protein structures deposited in the Protein Data Bank (PDB), the explosion of genomic sequencing and the rapid development of deep learning techniques to interpret these correlations. Despite these advances, contemporary physical and evolutionary-history-based approaches produce predictions that are far short of experimental accuracy in the majority of cases in which a close homologue has not been solved experimentally and this has limited their utility for many biological applications.

    In this study, we develop the first, to our knowledge, computational approach capable of predicting protein structures to near experimental accuracy in a majority of cases. The neural network AlphaFold that we developed was entered into the CASP14 assessment (May–July 2020; entered under

    Gary Yost

    American filmmaker and software designer

    Gary Yost (born 1959) is an American filmmaker, musician and software designer, best known for leading the team that created Autodesk 3ds Max.

    Antic Software

    Yost created the Antic Software publishing unit for Antic Magazine in 1984 after Jack Tramiel bought Atari Computer from Warner Communications and shut down the Atari Program Exchange.

    Yost met Tom Hudson at the Fall 1985 Comdex trade show and they began planning a suite of 3D animation tools for the Atari ST line of microcomputers, which became the Cyber Studio suite of animation products, beginning with CAD-3D 1.0, released autumn 1986. Stereo CAD-3D 2.0, released in late 1987, was built on an open-architecture framework and incorporated support for creating stereoscopic animations using the Tektronix “StereoTek” liquid crystal shutter 3D display. The StereoTek display was the first low-cost mass-market 3D display for microcomputers.

    The Yost Group, Autodesk and beyond

    In 1988 Yost left Antic Software to form “The Yost Group” when Autodesk offered him a software licensing agreement to create a suite of affordable animation tools for the IBM PC, beginning with Autodesk 3D Studio and Autodesk Animator, which was a 2D cel animation tool written by Jim Kent for The Yost Group. An obscure fact about Yost in 1988 is that, along with Computer Graphics pioneer Jim Blinn, he played percussion on the Todd Rundgren album "Nearly Human," which was recorded at Fantasy Studios in Berkeley, California.

    Working with Tom Hudson, Jack Powell, Dan Silva, Rolf Berteig and Gus Grubba, Yost led the team that created Autodesk 3D Studio versions 1-4 for the MS-DOS platform. Don Brittain, former VP of Research for Wavefront Technologies, was brought into the Yost Group to help create the re-designed 3D animation program called Autodesk 3ds Max, based on the Micr

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  • John Carmack

    American computer programmer and video game developer (born 1970)

    For other people named John Carmack, see John Carmack (disambiguation).

    John Carmack

    Carmack at the 2017 Game Developers Choice Awards

    Born (1970-08-21) August 21, 1970 (age 54)

    Shawnee Mission, Kansas, U.S.

    Occupation(s)Computer programmer, video game developer, engineer
    Years active1989–present
    Employer(s)Keen Technologies (2023–present)
    Oculus VR (2013–2022)
    Known forCo-founding id Software
    Commander Keen, Wolfenstein 3D, Doom, Quake, Rage
    TitleConsulting CTO, Oculus VR
    Founder, Armadillo Aerospace
    Political partyLibertarian
    Spouse
    PartnerTrista DeLeon (2022–present)
    Children2

    John D. Carmack II (born August 21, 1970) is an American computer programmer and video game developer. He co-founded the video game company id Software and was the lead programmer of its 1990s games Commander Keen, Wolfenstein 3D, Doom, Quake, and their sequels. Carmack made innovations in 3D computer graphics, such as his Carmack's Reverse algorithm for shadow volumes.

    In 2013, he resigned from id Software to work full-time at Oculus VR as their CTO. In 2019, he reduced his role to Consulting CTO so he could allocate more time toward artificial general intelligence (AGI). In 2022, he left Oculus to work on his AGI startup, Keen Technologies.

    Biography

    Early life

    Carmack was born in Shawnee Mission, Kansas, the son of local television news reporter Stan Carmack. He grew up in the Kansas City metropolitan area, where he became interested in computers at an early age. He attended Shawnee Mission East High School in Prairie Village, Kansas and Raytown South High School in nearby Raytown, Missouri.

    Carmack was introduced to video games with the 1978 shoot 'em up game Sp