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Palo Alto, CA, United States

Genencor is a biotechnology company based in Palo Alto, CA and a subsidiary of DuPont. Genencor is a leading producer of industrial enzymes and low-priced bulk protein. The name Genencor originates with Genencor, Inc., the original joint venture between Genentech and Corning Incorporated, which was founded in 1982. It is considered to have pioneered the field of industrial biotechnology, as distinct from traditional applications of biotechnology to health care and agriculture. Genencor ranks number 12 in revenues in the List of biotechnology companies. In 2008 Genencor entered a joint venture with DuPont, called DuPont Danisco Cellulosic Ethanol LLC, to develop and commercialize low cost technology for the production of cellulosic ethanol. In 2008, Genencor and Goodyear announced they are working to develop BioIsoprene. Wikipedia.

Chiang C.,Scripps Research Institute | Bongiorni C.,Scripps Research Institute | Bongiorni C.,Genencor | Perego M.,Scripps Research Institute
Journal of Bacteriology | Year: 2011

Sensing environmental conditions is an essential aspect of bacterial physiology and virulence. In Bacillus anthracis, the causative agent of anthrax, transcription of the two major virulence factors, toxin and capsule, is triggered by bicarbonate, a major compound in the mammalian body. Here it is shown that glucose is an additional signaling molecule recognized by B. anthracis for toxin synthesis. The presence of glucose increased the expression of the protective antigen toxin component-encoding gene (pagA) by stimulating induction of transcription of the AtxA virulence transcription factor. Induction of atxA transcription by glucose required the carbon catabolite protein CcpA via an indirect mechanism. CcpA did not bind specifically to any region of the extended atxA promoter. The virulence of a B. anthracis strain from which the ccpA gene was deleted was significantly attenuated in a mouse model of infection. The data demonstrated that glucose is an important host environment-derived signaling molecule and that CcpA is a molecular link between environmental sensing and B. anthracis pathogenesis. Copyright © 2011, American Society for Microbiology. All Rights Reserved. Source

Martin F.,University of Strasbourg | Barends S.,University of Strasbourg | Barends S.,Genencor | Jaeger S.,University of Strasbourg | And 3 more authors.
Molecular Cell | Year: 2011

In eukaryotes, a crucial step of translation initiation is the binding of the multifactor complex eIF4F to the 5′ end of the mRNA, a prerequisite to recruitment of the activated small ribosomal 43S particle. Histone H4 mRNAs have short 5′UTRs, which do not conform to the conventional scanning-initiation model. Here we show that the ORF of histone mRNA contains two structural elements critical for translation initiation. One of the two structures binds eIF4E without the need of the cap. Ribosomal 43S particles become tethered to this site and directly loaded in the vicinity of the AUG. The other structure, 19 nucleotides downstream of the initiation codon, forms a three-way helix junction, which sequesters the m 7G cap. This element facilitates direct positioning of the ribosome on the cognate start codon. This unusual translation initiation mode might be considered as a hybrid mechanism between the canonical and the IRES-driven translation initiation process. © 2011 Elsevier Inc. Source

Rege K.,Arizona State University | Heng M.,Genencor
Nature Protocols | Year: 2010

Methods development in chromatography is a time-consuming, trial-and-error process that requires laborious experimentation. We describe a high-throughput screening (HTS) protocol for the rapid identification of chromatographic steps for protein purification from cell-free expression broths. Broths containing the protein are loaded on different chromatographic resins aliquotted in membrane-bottomed microtiter plates. Serial step elution of protein from resins results in fraction collection in 96-well plates. Choice of the optimal chromatographic operating conditions is based on protein purity in eluted fractions, determined using SDS-PAGE analysis or similar analytical techniques. The screening procedure is then repeated in order to identify the subsequent chromatographic steps, ultimately leading to high purities of the protein. The protocol takes ∼24 h in order to determine the required sequence of chromatographic steps. The use of a miniaturized screen facilitates screening of a range of media and operating conditions (i.e., pH, salt concentration, and so on.) in parallel and is a novel approach to chromatographic methods development. © 2010 Nature Publishing Group. Source

Gicquel C.,Ecole Centrale Paris | Hege L.,Ecole Centrale Paris | Minoux M.,Laboratoire Dinformatique Of Paris 6 | Van Canneyt W.,Genencor
Computers and Operations Research | Year: 2012

We study a real-world complex hybrid flow-shop scheduling problem arising from a bio-process industry. There are a variety of constraints to be taken into account, in particular zero intermediate capacity and limited waiting time between processing stages. We propose an exact solution approach for this optimization problem, based on a discrete time representation and a mixed-integer linear programming formulation. The proposed solution algorithm makes use of a new family of valid inequalities exploiting the fact that a limited waiting time is imposed on jobs between two successive production stages. The results of our computational experiments confirm that the proposed method produces good feasible schedules for industrial instances. © 2011 Elsevier Ltd. All rights reserved. Source

Agency: Cordis | Branch: FP7 | Program: BSG-SME | Phase: SME-1 | Award Amount: 1.04M | Year: 2008

A competitive weapon for companies in process-intensive industries such as the chemical industry, is effective mastery of supply chain management from raw material to end product so as to improve efficiency, effectiveness, & profitability. However, in flow scheduling, the human operator can be overwhelmed by the complexity of the problem. CAP-SCHED involves developing a new intelligent scheduling system for companies in continuous/semi-continuous process industries. The innovative solution uses a multi-agent framework to combine 2 existing approaches which, individually, are inadequate to improve scheduling. However, combining both approaches offers significant improvements to implement more profitable solutions to scheduling problems, with better account taken of constraints. The 2 approaches are: 1. Simulation through trial & error: * The scheduler instructs the system to calculate all material flows in terms of quantity & quality from up- to down-stream throughout the plant; * If infeasibility occurs (e.g. capacity limitation) then the planner readjusts parameters in trial & error mode to reach a feasible solution. and 2. Algorithmic constraint solving: * the problem is represented as a mathematical model & the system attempts a solution, helped by heuristic guesses so as to guide the search algorithm via domain knowledge. The new idea is to allow full interaction with the system via a Graphical User Interface as if running in simulation mode, & to translate instructions, when the value of an operating parameter (or the starting date of an event) is fixed, in terms of constraints imposed in the mathematical model. Thus, the person responsible for scheduling can choose to fix variable values, and to let the system find those left free so as to reach a feasible solution. Overall, the solution will drastically reduce the need for multiple planning/scheduling loops so as to achieve a consistently optimised solution with improved profitability.

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