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Sunday, October 30, 2011


Collins; Revised edition (July 1, 2003) | ISBN: 0060555661 | English | PDF | 640 pages | 1.37 MB

The Intelligent Investor by Benjamin Graham published in 1949, is a widely acclaimed book on investing. Famous investor and billionaire Warren Buffett describes it as "by far the best book on investing ever written", a sentiment echoed by other Graham disciples such as Irving Kahn and Walter Schloss.

DOWNLOAD LINK:
http://uploading.com/files/1443e58b/6The_Intelligent_Investor.rar/

Saturday, October 29, 2011

image

Robert Bruce Thompson, "Illustrated Guide to Home Chemistry Experiments: All Lab, No Lecture"
O'R-il-y Media | 2008 | ISBN: 0596514921 | 432 pages | PDF | 11.77 Mb

For students, DIY hobbyists, and science buffs, who can no longer get real chemistry sets, this one-of-a-kind guide explains how to set up and use a home chemistry lab, with step-by-step instructions for conducting experiments in basic chemistry -- not just to make pretty colors and stinky smells, but to learn how to do real lab work:
• Purify alcohol by distillation
• Produce hydrogen and oxygen gas by electrolysis
• Smelt metallic copper from copper ore you make yourself
• Analyze the makeup of seawater, bone, and other common substances
• Synthesize oil of wintergreen from aspirin and rayon fiber from paper
• Perform forensics tests for fingerprints, blood, drugs, and poisons
From the 1930s through the 1970s, chemistry sets were among the most popular Christmas gifts, selling in the millions. But two decades ago, real chemistry sets began to disappear as manufacturers and retailers became concerned about liability. ,em>The Illustrated Guide to Home Chemistry Experiments steps up to the plate with lessons on how to equip your home chemistry lab, master laboratory skills, and work safely in your lab. The bulk of this book consists of 17 hands-on chapters that include multiple laboratory sessions on the following topics:
• Separating Mixtures
• Solubility and Solutions
• Colligative Properties of Solutions
• Introduction to Chemical Reactions & Stoichiometry
• Reduction-Oxidation (Redox) Reactions
• Acid-Base Chemistry
• Chemical Kinetics
• Chemical Equilibrium and Le Chatelier's Principle
• Gas Chemistry
• Thermochemistry and Calorimetry
• Electrochemistry
• Photochemistry
• Colloids and Suspensions
• Qualitative Analysis
• Quantitative Analysis
• Synthesis of Useful Compounds
• Forensic Chemistry
With plenty of full-color illustrations and photos, Illustrated Guide to Home Chemistry Experiments offers introductory level sessions suitable for a middle school or first-year high school chemistry laboratory course, and more advanced sessions suitable for students who intend to take the College Board Advanced Placement (AP) Chemistry exam. A student who completes all of the laboratories in this book will have done the equivalent of two full years of high school chemistry lab work or a first-year college general chemistry laboratory course.
This hands-on introduction to real chemistry -- using real equipment, real chemicals, and real quantitative experiments -- is ideal for the many thousands of young people and adults who want to experience the magic of chemistry.

FileSonic | EasyShare

Achieving Breakthrough Performance With Six Sigma

ASF file | 34.9MB | 100kbps | Audio MP3 | 128 kbps | CBR Stereo

DESCRIPTION:
What is Six Sigma? How is Six Sigma applicable to our organization? What is the Six Sigma process roadmap? What are the benefits of using a Six Sigma process?
Gary Gack, a Founder and Managing Partner of Six Sigma Advantage, explains the concepts of Six Sigma, and their application to business processes -- with a focus on software and IT. In interviews, Ken Edwards and Noah Hill of IDX Corporation describe how the software provider to hospitals and group practices is using Six Sigma to optimize development projects. Gack begins the program by defining Six Sigma, and showing how applying its principles drives bottom-line results. He explores the Six Sigma process roadmap, and then explains how the process is adapted for software and IT. Gack shows how organizations can use Six Sigma to evaluate the ‘voice of the customer,’ and balance it with the ‘voice of business.’ Next, he describes how to use Six Sigma for process improvement. Gack concludes with some key considerations for getting started with Six Sigma. This revised version of one of WatchIT’s most requested programs has been updated with new multimedia resources, such as Web links and white papers.
After watching this program, you will:
~ Understand the basics of the Six Sigma process;
~ Learn how to use Six Sigma for process improvement; and
~ Be able to evaluate its applicability to your company’s situation.
PROGRAM TOPICS:
INTRODUCTION
AGENDA
SIX SIGMA EXPERTS FEATURED IN THIS PROGRAM
PROGRAM ROI
WHAT IS SIX SIGMA?
Six Sigma Is a Cross-Discipline Framework
Six Sigma Frameworks: DMAIC and DMADV
Six Sigma Is a Process Metric
What Six Sigma Is Not
Why Should CIOs and Software IT Managers Care About Six Sigma?
THE SIX SIGMA PROCESS ROADMAP
Six Sigma Roadmap: Define Phase
Six Sigma Roadmap: Measure Phase
Six Sigma Roadmap: Analyze Phase
Six Sigma Roadmap: Is the Product or Process Capable?
Six Sigma Roadmap: Improve and Design Phases
Six Sigma Roadmap: Control and Verify Phases
Six Sigma Roadmap: Key Outcomes
SIX SIGMA CASE STUDY: IDX ENTERPRISE SOLUTIONS DIVISION
Ken Edwards: IDX Six Sigma Case Study
Noah Hill: IDX Six Sigma Case Study
Noah Hill: IDX Case Study – Use Six Sigma to Improve Client Support
Ken Edwards: IDX Case Study – Six Sigma Forces Interdepartmental Analysis
Ken Edwards: IDX Case Study – Six Sigma Approach Is Vital for Software Firms
Noah Hill: IDX Case Study – The Value of Strict Six Sigma Guidelines
Ken Edwards: IDX Case Study – Recommendations for Applying Six Sigma
WHAT IS DIFFERENT ABOUT SIX SIGMA FOR SOFTWARE AND IT
Factors Contributing to the High Rate of Software Project Failures
Six Sigma Addresses Obstacles to Software Project Improvement
Software Process Improvements Can Be Achieved With Six Sigma
USING SIX SIGMA TO EVALUATE THE VOICE OF THE CUSTOMER
Six Sigma Tool: Concept Selection Scorecard
Six Sigma Concept Selection Scorecard: Voice of the Customer Structure
Six Sigma Concept Selection Scorecard: Voice of the Customer – Kano Classifications
Six Sigma Concept Selection Scorecard: Voice of the Customer – Customer Importance
Six Sigma Concept Selection Scorecard: Voice of the Customer – Concept and Measures
Six Sigma Concept Selection Scorecard: Voice of the Customer – Size
Six Sigma Concept Selection Scorecard: Voice of the Customer – Customer Satisfaction
A Structured Six Sigma Scorecard Makes Complexity Manageable
Six Sigma Concept Selection Scorecard: Voice of the Customer – Business Value
Six Sigma Concept Selection Scorecard: Voice of the Customer – Feature Value Adjustment
Six Sigma Concept Selection Scorecard: Voice of the Customer – Overall Results
USING SIX SIGMA TO EVALUATE THE VOICE OF THE BUSINESS
Six Sigma Concept Selection Scorecard: Voice of the Business – Productivity Index
Six Sigma Concept Selection Scorecard: Voice of the Business – Schedule Compression
Six Sigma Concept Selection Scorecard: Voice of the Business Considerations
Six Sigma Concept Selection Scorecard: Objective Results for What-If Scenarios
Large Software Projects Reap Benefits From Six Sigma Scorecard Analysis
USING SIX SIGMA FOR PROCESS IMPROVEMENT
Using Six Sigma DMAIC to Improve Productivity
Six Sigma Tool: Defect Analysis Scorecard
Six Sigma Defect Analysis As-Is Scorecard: Defect Distribution
Six Sigma Defect Analysis As-Is Scorecard: Total Containment Effectiveness
Six Sigma Defect Analysis As-Is Scorecard: Defect Cost Analysis
Six Sigma Defect Analysis To-Be Scorecard: Defect Cost Analysis
Using Six Sigma DMAIC to Improve Productivity: Wrap-Up
KEY CONSIDERATIONS FOR GETTING STARTED WITH SIX SIGMA
Keys to Successful Six Sigma: Require a Sustained Corporate Initiative
Keys to Successful Six Sigma: Leverage the Six Sigma Language
Keys to Successful Six Sigma: Commit Time and Your Best Personnel
Keys to Successful Six Sigma: Use Aptly Trained Instructors
Keys to Successful Six Sigma: Integrate Additional Quality Initiatives
Download:
http://rapidshare.com/files/3348817/Achieving_Breakthrough_Performance_With_Six_Sigma.rar

Thursday, October 20, 2011

[+] Databases

Zinc Database, ChEMBL, CoCoCo, Protein DataBank (PDB), Binding MOAD (Mother Of All Database), Ligand Protein DataBase (LPDB), TTD, ...

[+] Chemical structure representations

ChemDraw, MarvinSketch, ACD/ChemSketch, ChemWriter, jsMolEditor, Marvin molecule editor and viewer, UCSF Chimera, Pymol, Swiss-PDB Viewer / DeepView, Daylight SMILES, InChI, Tripos Mol2, OpenBabel, LigPrep, Corina, PoseView, DS Visualizer, E-Babel, Corina online demo, Chemical Identifier Resolver, ChemMobi, ...

[+] Molecular Modeling

CHARMM, GROMACS, Amber, SwissParam, CHARMMing.org, Dundee PRODRG2 Server, ...

[+] Homology Modeling

Modeller, I-TASSER, ProModel, SWISS-MODEL, SWISS-MODEL Repository, ModBase, ...

[+] Binding site prediction

MED-SuMo, CAVER, FINDSITE, sc-PDB, CASTp, Pocketome, 3DLigandSite, metaPocket, PASS, ...

[+] Docking

Autodock, DOCK, GOLD, SwissDock, DockingServer, Blaster, ...

[+] Screening

CoLibri, Corina, Pharmer, Blaster, FINDSITE-LHM, e-LEA3D, ...

[+] Ligand design

GANDI, FlexNovo, BREED, Glide Fragment Library, e-LEA3D, 3DLigandSite, PASS, ...

[+] Binding free energy estimation

X-score, DrugScoreONLINE, BAPPL server, BAPPL-Z server, ...

[+] QSAR

cQSAR, clogP, ClogP/CMR, MOLE db, ChemDB/Datasets, Datasets from the Milano Chemometrics and QSAR Research Group, MolInfo, E-Dragon, Pattern Match Counter, ...

[-] ADME Toxicity

QikProp, q-ADME, q-TOX, ALOGPS, OSIRIS Property Explorer, ToxPredict, PK/DB, Leadscope Toxicity Database, The ADME databases, ...

Software

  • QikProp. Provides rapid ADME predictions of drug candidates. Distributed by Schrodinger.
  • q-ADME. Predicts the following properties: Drug half-life (T1/2); Fraction of oral dose absorbed (FA); Caco-2 permeability; Volume of distribution (VD); Octanol/water distribution coefficient (LogP).
  • q-TOX. Computes toxic effects of chemicals solely from their molecular structure (LD50, MRDD, side effects).
  • VolSurf. Calculate ADME Properties and Create Predictive ADME Models. Distributed by Tripos.
  • Metabolizer Preview. Enumerates all the possible metabolites of a given substrate, predicts the major metabolites and estimates metabolic stability. It can be used for the identification of metabolites by MS mass values, discovery of metabolically sensitive functionalities and toxicity prediction, and provide information related to the environmental effects of chemicals by bacterial degradation. Provided by ChemAxon.
  • ACD/PhysChem Suite. Predicts basic physicochemical properties, like pKa, logP, logD, aqueous solubility and other molecular properties in seconds, usr a fragment-based models. Distributed by ACD/Labs.
  • ACD/ADME Suite. Predicts of ADME properties from chemical structure, like Predict P-gp specificity, oral bioavailability, passive absorption, blood brain barrier permeation, distribution, P450 inhibitors, substrates and inhibitors, maximum recommended daily dose, Abraham-type (Absolv) solvation parameters. Distributed by ACD/Labs.
  • ACD/Tox Suite. Collection of software modules that predict probabilities for basic toxicity endpoints. Several modules including hERG Inhibition, CYP3A4 Inhibition, Genotoxicity, Acute Toxicity, Aquatic Toxicity, Eye/Skin Irritation, Endocrine System Disruption, and Health Effects. Distributed by ACD/Labs.
  • ACD/DMSO Solubility. Predicts solubility in DMSO solution. Distributed by ACD/Labs.
  • Sieve. Program for filtering out molecules with unwanted properties. Open source software distributed by Silicos.
  • ONTOMINE. Fingerprints-based data mining software used for automated Molecular Mining for BioActivity, Toxicity and Side effect prediction.
  • FAF-Drugs2. Free package for in silico ADMET filtering. Distributed by the university of Paris Diderot.
  • ADMET Predictor. Software for advanced predictive modeling of ADMET properties. Distributed by Simulations plus, Inc.
  • ClassPharmer. ClassPharmer is a cheminformatics platform for lead identification and prioritization, de novo design, scaffold hopping and lead optimization. The software is divided into four modules – Basic, SAR, Design and ADMET – each of which can be licensed separately. Distributed plu Simulation Plus, Inc.
  • GastroPlus. Simulates the oral absorption, pharmacokinetics, and pharmacodynamics for drugs in human and preclinical species. The underlying model is the Advanced Compartmental Absorption and Transit (ACAT) model. Distributed plu Simulation Plus, Inc.
  • Discovery Studio TOPKAT Software. Cross-validated models for the assessments of chemical toxicity from chemical's molecular structure. Distributed by Accelrys.
  • Discovery Studio ADMET Software. The ADMET Collection provides components that calculate predicted absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties for collections of molecules. Distributed by Accelrys.
  • PreADME. Calculates molecular descriptors. Predicts Drug-likeness. ADME predictions.
  • Molcode Toolbox. Molcode Toolbox allows prediction of medicinal and toxicological endpoints for a large variety of chemical structures, using proprietary QSAR models.
  • KOWWIN - EPI Suite. Estimates the log octanol-water partition coefficient of chemicals using an atom/fragment contribution method. Distributed by the EPA~s Office of Pollution Prevention Toxics and Syracuse Research Corporation (SRC) as part of the EPI Suite. For Windows.
  • ChemTree. Predicts ADME/Tox properties using QSAR. Distributed by Golden Helix.
  • OncoLogic. Evaluates the likelihood that a chemical may cause cancer, using SAR analysis, experts decision mimicking and knowledge of how chemicals cause cancer in animals and humans. Distributed for free by the US Environmental Protection Agency (EPA).
  • HazardExpert Pro. Predicts the toxicity of organic compounds based on toxic fragments. Distributed by CompuDrug.
  • MetabolExpert. Predicts the most common metabolic pathways in animals, plants or through photodegradation. Distributed by CompuDrug.
  • MEXAlert. Identifies compounds that have a high probability of being eliminated from the body in a first pass through the liver and kidney. Distributed by CompuDrug.
  • PrologP/PrologD. Predicts the logP/logD values using a combination of linear and neural network methods. Distributed by CompuDrug.
  • Leadscope. Estimates toxiticy using QSAR. Distributed by Leadscope.
  • COMPACT. Identifies potential carcinogenicity or toxicities mediated by CYP450s.
  • CASETOX. Uses MCASE to predict toxicity. Distributed by MultiCASE.
  • META. Predicts metabolic paths of molecules. Distributed by MultiCASE.
  • PK-Sim. Predicts ADMET properties. Distributed by Bayer technology Services.
  • SimCYP. The SimCYP Population-based ADME Simulator is a platform for the prediction of drug-drug interactions and pharmacokinetic outcomes in clinical populations. Distributed by SimCYP.
  • Cloe Predict. Pharmacokinetic prediction using phisiologically based pharmacokinetic modeling (PBPK), and prediction of human intestinal absorption using solubility, pKa and Caco-2 permeability data. Distributed by Cyprotex Discovery.
  • KnowItAll - ADME | Tox Edition. Prediction of ADME Tox properties using consensus modeling. Distributed by Bio-Rad Laboratories.
  • PASS. Identification of probable targets and mechanisms of toxicity.
  • MetaDrug. Predicts toxicity and metabolism of compounds using >70 QSAR models for ADME/Tox properties. Distributed by GeneGo.
  • ADMEWORKS ModelBuilder. Builds QSAR/QSPR models that can later be used for predicting various chemical and biological properties of compounds. Models are based on values of physicochemical, topological, geometrical, and electronic properties derived from the molecular structure, and can be imported into ADMEWORKS Predictor.
  • ADMEWORKS Predictor. Virtual (in silico) screening system intended for simultaneous evaluation of the ADMET properties of compounds. It complements existing in silico technologies for evaluating pharmacological properties.
  • MetaSite. Computational procedure that predicts metabolic transformations related to cytochrome-mediated reactions in phase I metabolism. The method predicts "hot spots" in the molecule, suggests the regions that contribute most towards each "hot spot", providing additional derivation sites for chemists to design new stable compounds, predicts the structures of the most likely metabolites and warns about the potential of CYP mechanism-based inhibition. Distributed by Moldiscovery.

Web services

  • ALOGPS. On-line prediction of logP, water solubility and pKa(s) of compounds for drug design (ADME/T and HTS) and environmental chemistry studies. ALOGPS also displays values calculated with Pharma Algorithms LogP, LogS and pKa, Actelion LogP & LogS (many thanks to Dr Thomas Sander), Molinspiration logP, KOWWIN logP, ALOGP (Viswanadhan et al, 1989), MLOGP (Moriguchi et al, 1992) implemented in the DragonX software, XLOGP2 and XLOGP3 programs and ChemAxon logP calculator
  • OSIRIS Property Explorer. Integral part of Actelion's inhouse substance registration system. Calculates on-the-fly various drug-relevant properties for drawn chemical structures, including some toxicity and druglikeness properties. Maintained by the Virtual Computational Chemistry Laboratory.
  • ToxPredict. Web service to estimate toxicological hazard of a chemical structure. Molecules can be drawn, or input by any identifier (CAS, Name, EINECS) or SMILES or InChI or URL of OpenTox compound or dataset. Provided by OpenTox.
  • ToxCreate. Web service to create computational models to predict toxicity. Provided by OpenTox.
  • ADME-Tox. ADME-Tox (poor absorption, distribution, metabolism, elimination (ADME) or toxicity) filtering for small compounds, based on a set of elementary rules.
  • STITCH. Resource to explore known and predicted interactions of chemicals and proteins. Chemicals are linked to other chemicals and proteins by evidence derived from experiments, databases and the literature. STITCH contains interactions for over 74,000 small molecules and over 2.5 million proteins in 630 organisms.
  • XScore-LogP. Calculates the octanol/water partition coefficient for a drug, based on a feature of the X-Score program.
  • VirtualToxLab. ''In silico'' tool for predicting the toxic (endocrine-disrupting) potential of existing and hypothetical compounds (drugs, chemicals, natural products) by simulating and quantifying their interactions towards a series of proteins known to trigger adverse effects using automated, flexible docking combined with multi-dimensional QSAR (mQSAR).
  • PharmMapper. Freely accessed web-server designed to identify potential target candidates for the given probe small molecules (drugs, natural products, or other newly discovered compounds with binding targets unidentified) using pharmacophore mapping approach.
  • MODEL - Molecular Descriptor Lab. Computes structural and physichemical properties of molecules from their 3D structures.
  • PreADMET. Web-based application for predicting ADME data and building drug-like library using in silico method.
  • Free ADME Tools. ADME Prediction Toolbox of the SimCYP application provided free of charge by SimCYP.
  • UM-BBD Pathway Prediction System. The PPS predicts plausible pathways for microbial degradation of chemical compounds. Predictions use biotransformation rules, based on reactions found in the UM-BBD database or in the scientific literature. Provided by the University of Minnesota.
  • MetaPrint2D. Metabolic site predictor. MetaPrint2D is a tool that predicts xenobiotic metabolism through data-mining and statistical analysis of known metabolic transformations reported in scientific literature. MetaPrint2D-React can make predictions concerning a wider range of reactions than MetaPrint2D, and is able to predict the types of transformation that can take place at each site of metabolism, and the likely metabolite formed. Provided by the University of Cambridge.
  • MetaPrint2D-React.. Metabolic site predictor. MetaPrint2D is a tool that predicts xenobiotic metabolism through data-mining and statistical analysis of known metabolic transformations reported in scientific literature. MetaPrint2D, which predicts sites of phase I metabolism, defined as the addition of oxygen (e.g. hydroxylation, oxidation, epoxidation) or elimination reactions. Provided by the University of Cambridge.

Databases

  • PK/DB. Freely available database for pharmacokinetic properties, designed with the aim of creating robust databases for pharmacokinetic studies and in silico ADME (Absorption, Distribution, Metabolism, and Excretion) prediction.
  • Leadscope Toxicity Database. Database of 160,000 chemical structures with toxicity data. Distributed by Leadscope.
  • The ADME databases. Databases for benchmarking the results of experiments, validating the accuracy of existing ADME predictive models, and building new predictive models.
  • The ADME database. Provides comprehensive data for structurally diverse compounds associated with known ADME properties, including human oral bioavailability, enzymes metabolism, inhibition and induction, transport, plasma protein binding and bloodbrain barrier. Distributed by Aureus.
  • SuperTarget Database. Database of about 7300 drug-target relations.
  • SIDER. (Side Effect Resource). contains information on marketed medicines and their recorded adverse drug reactions. The information is extracted from public documents and package inserts. The available information include side effect frequency, drug and side effect classifications as well as links to further information, for example drug–target relations.
  • ADME DB. Database containing data on interactions of substances with Drug Metabolizing Enzymes and Drug Transporters. It is designed for use in drug research and development, including drug-drug interactions and ADME (Absorption, Distribution, Metabolism and Excretion) studies.
  • SAR Genetox Database. Genetic toxicity database to be used as a resource for developing predictive modeling training sets. Distributed by Leadscope.
  • SAR Carcinogenicity Database. Carcinogenicity database with validated structures to be used as a resource for preparing training sets. Distributed by Leadscope.

Wednesday, October 12, 2011

The new version of the CAESAR models, that will be made freely available soon, will include some new features, helpful both to improve usability of the software and to obtain more reliable predictions.

TRY CAESAR v2.0USE THE CURRENT VERSION

Importing and loading structures

With CAESAR 2.0 you will be able to submit molecules in many different ways:

  • Import multiple molecules in sdf and/or smi file format
  • Draw structure using the internal editor*
  • Enter molecules one-by-one using SMILES format, molecule name (IUPAC) and CAS number

* The molecule editor included is part of the ChemAxon Marvin package.
More info at http://www.chemaxon.com/marvin/help/index.html

The image on the right, as well as all the images used as preview in this page, refers to the stand-alone version of CAESAR software, which anticipate most of the new features of CAESAR 2.0.

Results reliability & model applicability domain


According to REACH, user should check if "the substance is included in the applicability domain of the model", for a correct use of the (quantitative) structure-activity relationship (Q)SAR model.
CAESAR 2.0 integrates a tool to assess the applicability domain (AD), through quantitative and visual ways. This free tool is based on:

  • Chemiometric check,
  • Fragments for outliers,
  • Similarity index,
  • Prediction Concordance with experimental values,
  • Prediction Accuracy of the prediction,
  • Uncertainty of the prediction.

Thus, the CAESAR's tool is based not only on the chemical information, as the typical AD tools, but also on toxicity results.
Furthermore, it uses not only a priori data (from the chemical structure), but also a posteriori ones, from the results of the models. This tool proved to discriminate cases where QSAR can be applied, and cases were there may be problems.

WARNING: the MUTAGENICITY model could classify a compound as mutagen even if it is formally out of the applicability domain. This behaviour is normal for this model and it is related to the use of structural alerts [ref.].

Apart from this new feature, the user could still compare the prediction obtained for a molecule with those obtained for its six most similar molecules founded in the dataset used to build the model, as in the current version of CAESAR models.

Most of the new features that will be present in the new CAESAR v2.0 software have been integrated in the stand-alone models for Developmental Toxicity and Mutagenicity

The stand-alone version of CAESAR can be downloaded for free and have been developed to work off-line. The CAS number input method is not available for this version of the software.

If you need help using the software, you can use the video tutorials we have prepared, that will guide you step-by-step explaining exactly how to use the CAESAR stand-alone software.

DOWNLOAD NOW CAESAR v2.0
Download the stand-alone version of the CAESAR v2.0 QSAR model. This version could be run locally with no internet connection needs.
Stand-alone version of the other CAESAR models will be available in the next future.

DEVELOPMENTAL TOXICITY

DOWNLOAD

SIZE: ~100 Mbyte

HELP

MUTAGENICITY

DOWNLOAD

SIZE: ~156 Mbyte

HELP

COMMON PROBLEMS AND SOLUTIONS

Problem importing structures using "import structure(s) from file".

Software requirements / specs:

  • Works on Windows / Mac / Linux systems
  •  
  • Needs JAVA™ 1.5 or higher to run. Click here to download.
  • The stand-alone version works on 32bit systems only.

If you need any information and/or support, please contact: coord@caesar-project.eu.

The CAESAR application has been developed by:

  • Davide Bigoni (Bigoni Consulting) - Client/Server infrastructure and services
  • Alberto Manganaro (IRFMN) - Implementation of Models, Molecular Descriptors and Applicability Domain
  • Antonio Cassano (IRFMN) - Implementation of Stand-alone versions
  • Todd Martin (US EPA) - Implementation of Molecular Descriptors
  • Alexandros Spiliopoulos (University of Patras) - Contribution to the implementation of Developmnetal Toxicity stand-alone
  • Aris Avlonitis (University of Patras) - Contribution to the implementation of Developmnetal Toxicity stand-alone
  • Adriana Gomez Delgado (AGDesigner) - Graphic layout
  • Vittorio Castiglioni (IRFMN) - Graphic contribution for the stand-alone

All the models implemented have been developed by the CAESAR consortium.

Toxtree

Toxtree is a flexible and user-friendly open-source application that places chemicals into categories and predicts various kinds of toxic effect by applying decision tree approaches. The following decision trees are currently implemented:

    • the Kroes TTC decision tree
    • the Verhaar scheme for aquatic modes of action
    • rulebases for skin and eye irritation and corrosion
    • the Benigni-Bossa rulebase for mutagenicity and carcinogenicity
    • the ToxMic rulebase for the in vivo micronucleus assay
    • structural alerts for identification of Michael Acceptors
    • the START rulebase for persistance / biodegradation potential
    • structural alerts for the identification of organic functional groups (ISSFUNC rulebase)


Toxtree

Toxtree was developed by Ideaconsult Ltd (Sofia, Bulgaria) under the terms of a JRC contract. The software is made freely available as a service to scientific researchers and anyone with an interest in the application of computer-based estimation methods in the assessment of chemical toxicity.

Toxtree (Version 2.5.0) (August 2011)

Toxtree 2.5.0 is a standalone software application that can be run on the Microsoft Windows operating system as well as other platforms with the Java 2 Runtime Environment (Standard Edition 1.5 or newer) installed.
Toxtree 2.5.0 can be downloaded from the Sourceforge website:

Toxtree (Version 1.60) - Download area (July 2009)


The Toxtree software can be downloaded (free of charge) from this website. Toxtree 1.60 is a standalone software application that can be run on the Microsoft Windows operating system as well as other platforms with the Java Runtime Environment (Standard Edition 1.5 or newer) installed.
The setup ("exe") file contains all the required packages for Windows, including the Java(TM) Runtime Environment (JRE 5.0). The archive ("zip") file is an archive of the program without the Windows installer; this can be used to run the program also on a Unix/Linux platform.


In addition to the rulebases already implemented in Toxtree 1.60, the following plug-in was developed by the Istituto Superiore di Sanita' (Rome, Italy) to provide a means of identifying organic functional groups. The ISSFUNC rulebase is a functional groups profiler that implements a set of 204 organic functional groups recognised by the "Checkmol" program, developed by Norbert Haider (University of Vienna, Austria). The jar file should be placed in the "Toxtree\ext\" directory of the Toxtree installation.

Feedback


Please report any comments, enquiries or bug reports via the dedicated Sourceforge webpage.

Key features
    • Easy to install.
    • Easy to follow manual provided.
    • End-user modifications of the tree possible (by adding new structural rules).
    • Classification of chemical structures by an interactive 2D graphical editor.
    • Batch mode classification possible; CSV, TXT or SDF file formats supported.
    • Results (with classification path explained) viewable in a graphical user interface or saved (file formats supported: CSV, SDF or TXT).
    • Implementation of Cramer decision tree approach to estimate toxic hazard.
    • Implementation of Verhaar scheme for modes of toxic action.
    • Implementation of BfR and SICRET rules to predict skin irritation and corrosion.
    • Implementation of BfR rules to predict eye irritation and corrosion.
    • Implementation of Benigni-Bossa rules to predict mutagenicity and carcinogenicity.
Copyright and Disclaimer Notice


Toxtree is open source software; you are authorised to redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 (June 1991) of the License, or any later version. For more details, see the GNU General Public License at http://www.gnu.org/licenses/gpl.txt.
We request that proper credit is given to the copyright and authorship for Toxtree. This includes adding the following copyright notice to the beginning of your source code files, and to any copyright notice that you may distribute with programs based on this work:

    Developed by Dr Nina Jeliazkova (Ideaconsult Ltd; contact nina@acad.bg) on behalf of the Joint Research Centre (JRC). Copyright European Union (2005, 2007 & 2008).


The Toxtree software is made available by the JRC as a service to the worldwide scientific and regulatory communities. The JRC and European Communities provide no technical support, warranties or remedies for this software. It does not imply any endorsement or acceptance by the JRC or by the European Commission of the algorithms encoded in the software. The European Commission shall not be liable to the User or any third party for any direct or indirect, special, incidental, punitive, cover or consequential damages, arising out of the use of, or inability to use, Toxtree.

References
  1. Benigni R, Bossa C, Jeliazkova N, Netzeva T & Worth A (2008). The Benigni / Bossa rulebase for mutagenicity and carcinogenicity - a module of Toxtree. European Commission report EUR 23241 EN.

    Download paper

  2. Patlewicz G, Jeliazkova N, Safford RJ, Worth AP & Aleksiev B (2008). An evaluation of the implementation of the Cramer classification scheme in the Toxtree software. SAR and QSAR in Environmental Research 19, 495-524
  3. Cramer GM, Ford RA & Hall RL (1978) Estimation of Toxic Hazard - A Decision Tree Approach. Food and Cosmetics Toxicology 16, 255-276.
  4. Gerner I, Liebsch M & Spielmann H (2005). Assessment of the eye irritating properties of chemicals by applying alternatives to the Draize rabbit eye test: the use of QSARs and in vitro tests for the classification of eye irritation. ATLA 33, 215-237.
  5. Verhaar HJM, van Leeuwen CJ & Hermens JLM (1992). Classifying environmental pollutants. 1. Structure-activity relationships for prediction of aquatic toxicity. Chemosphere 25, 471-491.
  6. Verhaar HJM, Mulder W & Hermens JLM (1995). QSARs for ecotoxicity. In: Overview of structure-activity relationships for environmental endpoints, Part 1: General outline and procedure. Hermens JLM (Ed), Report prepared within the framework of the project "QSAR for Prediction of Fate and Effects of Chemicals in the Environment", an international project of the Environment; Technologies RTD Programme (DGXII/D-1) of the European Commission under contract number EV5V-CT92-0211.
  7. Verhaar HJM, Solbe J, Speksnijder J, van Leeuwen CJ & Hermens JLM (2000). Classifying environmental pollutants: Part 3. External validation of the classification system. Chemosphere 40, 875-883.
  8. Walker JD, Gerner I, Hulzebos E & Schlegel K (2005). The Skin Irritation Corrosion Rules Estimation Tool (SICRET). QSAR Comb. Sci. 24, 378-384.

SHOW: FREE SOFTWARE ONLY ALL SOFTWARE

Physico-chemical properties

7.2 MELTING/FREEZING POINT

7.3 BOILING POINT

7.4 RELATIVE DENSITY

7.5 VAPOUR PRESSURE

7.6 SURFACE TENSION

7.7 WATER SOLUBILITY

7.8 PARTITION COEFFICIENT n-Octanol/Water

7.9 FLASH POINT

7.16 DISSOCIATION CONSTANT

7.17 VISCOSITY

Toxicological group

8.1 SKIN IRRITATION or SKIN CORROSION

8.2 EYE-IRRITATION

8.3 SKIN SENSITIZATION

8.4 MUTAGENICITY

8.4.1 IN-VITRO GENE MUTATION STUDY IN BACTERIA

8.4.2 IN-VITRO CITOGENICITY STUDY IN MAMMALIAN CELLS OR IN-VITRO MICRONUCLEUS STUDY

8.4.4 IN-VIVO MUTAGENICITY STUDY

8.5 ACUTE TOXICITY

8.5.1 ACUTE TOXICITY (by oral route)

8.5.2 ACUTE TOXICITY (by inhalation)

8.6 REPEATED DOSE TOXICITY

8.6.1 SHORT-TERM REPEATED DOSE TOXICITY (28 DAYS)

8.6.2 SUB-CHRONIC TOXICITY STUDY (90 DAYS)

8.6.3 LONG-TERM REPEATED DOSE TOXICITY STUDY (>12 MONTHS)

8.7 REPRODUCTIVE TOXICITY

8.7.1 SCREENING FOR REPRODUCTIVE/DEVELOPMENTAL TOXICITY (OECD 412 - 422)

8.7.2 PRE-NATAL DEVELOPMENTAL TOXICITY STUDY (OECD 414)

8.8 TOXICOKINETICS

8.8.1 ASSESSMENT OF TOXICOKINETIC BEHAVIOR OF THE SUBSTANCE

8.9 CARCINOGENICITY

Environmental Properties & Ecotoxicological Group

9.1 AQUATIC TOXICITY

9.1.1 SHORT-TERM TOXICITY TESTING ON INVERTEBRATES (DAPHNIA)

9.1.2 GROWTH INHIBITION STUDY AQUATIC PLANT (ALGAE PREFERRED)

9.1.3 SHORT-TERM TOXICITY TESTING ON FISH

9.1.4 ACTIVATED SLUDGE RESPIRATION INHIBITION TESTING

9.1.5 LONG-TERM TOXICITY TESTING ON INVERTEBRATES (PREFERRED DAPHNIA)

9.1.6 LONG-TERM TOXICITY TESTING ON FISH

9.2 DEGRADATION [9.2.1 BIOTIC & 9.2.2 ABIOTIC]

9.2.1.1 READY BIODEGRADABILITY

9.2.1.3 SOIL SIMULATION TESTING

9.2.2 ABIOTIC DEGRADATION

9.2.2.1 HYDROLYSIS AS A FUNCTION OF pH

9.2.3 IDENTIFICATION OF DEGRADATION PRODUCTS

9.3 FATE AND BEHAVIOUR IN THE ENVIRONMENT

9.3.1 ABSORPTION / DESORPTION SCREENING

9.3.2 BIOACCUMULATION IN AQUATIC SPECIES, PREFERABLE FISH

9.3.4 FURTHER INFORMATION ON THE ENVIRONMENTAL FATE AND BEHAVIOUR OF THE SUBSTANCE

9.4 EFFECTS ON TERRESTRIAL ORGANISMS

9.4.1 SHORT-TERM TOXICITY TO INVERTEBRATES

9.4.3 SHORT-TERM TOXICITY TO PLANTS

Free Toxicity Prediction Software

Quantitative Structure Activity Relationship

Introduction
Quantitative Structure Activity Relationships (QSARs) are mathematical models that are used to predict measures of toxicity from physical characteristics of the structure of chemicals (known as molecular descriptors). Acute toxicities (such as the concentration that causes half of a fish population to die) are one example of the toxicity measures that may be predicted from QSARs. Simple QSAR models calculate the toxicity of chemicals using a simple linear function of molecular descriptors:

Toxicity = ax1+bx2+c

where x1 and x2 are the independent descriptor variables and a, b, and c are fitted parameters. Examples of molecular descriptors include the molecular weight and the octanol-water partition coefficient. Additional examples are provided in our Molecular Descriptors Guide (PDF) (47 pp, 279 KB).

Uses of QSAR toxicity models
  • QSAR toxicity predictions may be used to screen untested compounds in order to establish priorities for traditional bioassays, which are expensive and time-consuming.
  • QSAR models are useful for estimating toxicities needed for green process design algorithms such as the Waste Reduction Algorithm.
Objectives
  • Develop quantitative structure activity relationship (QSAR) methodologies to estimate toxicity from molecular structure
  • Develop software, such as the Toxicity Estimation Software Tool (T.E.S.T.), that will enable users to easily estimate toxicity from molecular structure
QSAR Methodologies

Several QSAR methodologies have been developed:

  • Hierarchical method - The toxicity for a given query compound is estimated using the weighted average of the predictions from several different models. The different models are obtained by using Ward’s method to divide the training set into a series of structurally similar clusters. A genetic algorithm-based technique is used to generate models for each cluster. The models are generated prior to runtime.
  • FDA method - The prediction for each test chemical is made using a new model that is fit to the chemicals that are most similar to the test compound. Each model is generated at runtime.
  • Single-model method - Predictions are made using a multilinear regression model that is fit to the training set (using molecular descriptors as independent variables) using a genetic algorithm-based approach. The regression model is generated prior to runtime.
  • Group contribution method - Predictions are made using a multilinear regression model that is fit to the training set (using molecular fragment counts as independent variables). The regression model is generated prior to runtime.
  • Nearest neighbor method - The predicted toxicity is estimated by taking an average of the three chemicals in the training set that are most similar to the test chemical.
  • Consensus method - The predicted toxicity is estimated by taking an average of the predicted toxicities from each of the above QSAR methodologies.
  • CAESAR Project logoRandom forest method- The predicted toxicity is estimated using a decision tree which bins a chemical into a certain toxicity score (i.e. positive or negative developmental toxicity) using a set of molecular descriptors as decision variables. The random forest method is currently only available for the developmental toxicity endpoint. The random forest model for the developmental toxicity endpoint was developed by researchers at Mario Negri Institute for Pharmacological Research as part of the CAESAR project. Exit EPA Disclaimer

These methodologies are explained in detail in the publications below.

Toxicity Estimation Software Tool (T.E.S.T.)

T.E.S.T. will enable users to easily estimate acute toxicity using the above QSAR methodologies. The software is now available for download. The software is described in further detail in the User's Guide (PDF) (66 pp, 540 KB).The software is based on the Chemistry Development Kit exit EPA, an open-source Java library for computational chemistry.

The software includes models for the following endpoints:

  • 96-hour fathead minnow 50% lethal concentration (LC50)
  • 48-hour daphnia magna 50% lethal concentration (LC50)
  • Tetrahymena pyriformis 50% growth inhibition concentration (IGC50) Exit EPA Disclaimer
  • Oral rat 50% lethal dose (LD50) Exit EPA Disclaimer
  • Bioconcentration Factor (BCF). The bioconcentration factor data set was compiled by researchers at the Mario Negri Isituto Di Ricerche Farmacologiche.Exit EPA Disclaimer
  • Developmental Toxicity (DevTox). Exit EPA Disclaimer
  • Ames mutagenicity (Mutagenicity).Exit EPA Disclaimer

The software now contains models for the following physical properties:

Models for additional endpoints will be added as they are completed.

envelope Get email alerts when new versions of the T.E.S.T. software are posted.

Download T.E.S.T (version 4.0):

The training and prediction sets used in the software are available here.

Sample structure data files (such as a MDL SD file) are available here.

What's new in Version 4.0?
  • Physical properties are now estimated
  • Batch mode is improved:
    • Loading can now be interrupted
    • Chemicals with loading errors are displayed at the top of the batch table
    • Can now load SMILES files with no identifier field (chemicals are assigned arbitrary IDs)
  • Aromaticity detection is improved:
    • Can handle aromatic bond orders (bond order = 4) in mol or sd files
    • The SMILES parser has been improved to better handle complicated aromatic ring systems
  • Added Options screen:
    • Added ability to change the output directory after it has been set
    • The program now remembers the previously selected output folder
    • The "Relax fragment constraint" checkbox was moved to Options screen
Prior Version History
  • 3.3 (7/8/10)
    • Daphnia magna LC50 endpoint was added
    • AMES Mutagenicity endpoint was added
    • The following changes were made for binary endpoints such as developmental toxicity and AMES mutagenicity:
      • QSAR models now have stricter statistical standards (leave one out concordance = 0.8, sensitivity = 0.5, and specificity = 0.5)
      • Model statistics such as concordance, sensitivity, and specificity are now displayed in the results web pages
  • 3.2 (12/18/09)
    • Reproductive toxicity endpoint was added
    • Random forest QSAR method was added (for reproductive toxicity endpoint only)
  • 3.1 (6/23/09)
    • Fixed issue with running TEST in non-english speaking countries
  • 3.0 (4/14/09)
    • Random selection is used to divide the data sets into training and test sets
    • Added BCF endpoint
    • Added consensus prediction method
  • 2.0 (2/24/09)
    • Each toxicity data set is now split into a training and test set.
    • The toxicity models included in the software are now fit to the training sets (previously they were fit to the overall sets)
    • The batch mode was improved (chemicals can be added and the list can now be saved as an SDF)
  • 1.0.3 (10/24/08)
    • Fixed calculation of "ieadje" molecular descriptor
    • Fixed definitions of chi descriptors in numbered list in molecular descriptors guide
System requirements
  • Java version 1.6 or higher exit EPA
  • Memory:
    • For Windows XP®, 1 GB of RAM is recommended.
    • For Windows Vista®, 2 GB of RAM is recommended.
Installation Instructions
  1. Save the appropriate installation file to your hard drive. Due to the large size of the file, the download may take 15 minutes or longer depending on the speed of the connection.
  2. Double-click the installation file (for Linux users: open a shell, cd to the directory where you downloaded the installer and at the prompt type: sh ./install.bin).
Silent Installation Instructions for Network Administrators (for Windows users)
  1. The software can be installed silently by issuing the following command at the command prompt:
    install -i silent
Publications

Sushko, I.; Novotarskyi1, S.; Körner, R.; Pandey, A. K.; Cherkasov, A.; Li, J.; Gramatica, P.; Hansen, K.; Schroeter, T.; Müller, K.-R.; Xi, L.; Liu, H; Yao, X.; Öberg, T.; Hormozdiari, F.; Dao, F.; Sahinalp, C.; Todeschini, R.; Polishchuk, P.; Artemenko, A.; Kuz’min, V.; Martin, T.M.; Young, D. M.; Fourches, D.; Muratov, E.; Tropsha, A.; Baskin, I.; Horvath, D.; Marcou, G.; Varnek, A; Prokopenko, V. V.; Tetko, I.V. (2010). “Applicability domains for classification problems: benchmarking of distance to models for AMES mutagenicity set.” J. Chem. Inf. Model, 50, 2094-2111.

Cassano, A.; Manganaro, A; Martin, T.; Young, D.; Piclin, N.; Pintore, M.; Bigoni, D.; Benfenati, E. (2010). “The CAESAR models for developmental toxicity.” Chemistry Central Journal, 4(Suppl 1):S4.

Zhu, H.; Martin, T.M.; Young, D. M.; Tropsha, A. (2009). “Combinatorial QSAR Modeling of Rat Acute Toxicity by Oral Exposure.“ Chemical Research in Toxicology, 22 (12), pp 1913-1921.

Benfenati, E., Benigni, R., Demarini, D.M., Helma, C., Kirkland, D., Martin, T.M., Mazzatorta, G., Ouedraogo-Arras, G., Richard, A.M., Schilter, B., Schoonen, W.G.E.J., Snyder, R.D., and C. Yang. (2009). “Predictive Models for Carcinogenicity and Mutagenicity: Frameworks, State-of-the-Art, and Perspectives.” Journal of Environmental Science and Health Part C, 27, 2: 57-90.

Young, D.M.; Martin, T.M.; Venkatapathy, R.; Harten, P. (2008) “Are the Chemical Structures in your QSAR Correct?” QSAR & Combinatorial Science, 27 (11-12), 1337-1345.

Martin,T.M., P. Harten, R. Venkatapathy, S. Das and D.M. Young. (2008). “A Hierarchical Clustering Methodology for the Estimation of Toxicity.” Toxicology Mechanisms and Methods, 18, 2: 251–266.

Martin, T.M., and D.M. Young. (2001). “Prediction of the Acute Toxicity (96-h LC50) of Organic Compounds in the Fathead Minnow (Pimephales Promelas) Using a Group Contribution Method.” Chemical Research in Toxicology, 14, 10: 1378–1385.

Contact

Todd Martin, PhD.
Research Chemical Engineer

Friday, October 7, 2011

Death is very likely the single best invention of Life-Steve Jobs

We Miss You"GENIUS OF THE CENTURY&A DESIGNER AT HEART"

“No one wants to die. Even people who want to go to heaven don’t want to die to get there. And yet death is the destination we all share. No one has ever escaped it. And that is as it should be, because Death is very likely the single best invention of Life. It is Life’s change agent. It clears out the old to make way for the new. Right now the new is you, but someday not too long from now, you will gradually become the old and be cleared away. Sorry to be so dramatic, but it is quite true.

“Your time is limited, so don’t waste it living someone else’s life. Don’t be trapped by dogma — which is living with the results of other people’s thinking. Don’t let the noise of others’ opinions drown out your own inner voice. And most important, have the courage to follow your heart and intuition. They somehow already know what you truly want to become. Everything else is secondary.

Here is the full text of the above speech from Stanford website: http://news.stanford.edu/news/2005/june15/jobs-061505.html

Here is A Photo Biography Of The Great Steve Jobs:http://www.businessinsider.com/a-photo-biography-of-the-great-steve-jobs-2011-10#steves-childhood-home-1

Here are Steve Jobs: Top 10 Innovations, From the Apple II to the iPod to iPad : http://abcnews.go.com/Technology/steve-jobs-death-top-10-products-including-apple/story?id=14680924#




Jeffrey S. Young, William L. Simon, "iCon Steve Jobs: The Greatest Second Act in the History of Business"
Wiley | 2005-05-23 | ISBN: 0471720836 | 368 pages | PDF | 25 MB
"My books are about the secret lives of hackers. This book is about the secret life of maybe the most influential person in technology. Who else can you think of that has put his stamp on three industries – computers, music, and movie animation? Once you start reading, you won’t want to put it down."-- Kevin Mitnick, security consultant, www.mitnicksecurity.com, author of The Art of Deception and The Art of Intrusion

"Assembling the artifacts and stories to showcase the achievements of man is the work of museums like ours. But history also relies on authors like Young and Simon, who have done a memorable job compiling the biography of Steven Jobs from conversations with the people who have been players with this extraordinary technology pioneer. And this book is a fascinating read as well."-- John Toole, executive director and CEO, Computer History Museum, Mountain View, California

"During the high-tech boom years when Steve Jobs gained global recognition, I was on the Silicon Valley scene to witness his rise to fame. We all admired his genius and became aware of his flaws, as well. You won’t want to miss this absorbing behind-the-scenes story." -- Steve Westly, controller of the state of California, former senior vice president, eBay

"If technology was a competitive sport, Steve Jobs would be a combination of an NBA misbehaving superstar and an NHL player who high-sticks opponents whenever he thinks they’ve treated him badly. But he’d also be MVP. Fascinating and unforgettable." -- Carol Mitch, Best Damn Sports Show Period

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Barbara Sheen, "Steve Jobs"
Lucent | 2009-10-16 | ISBN: 1420501607 | 96 pages | PDF | 6,8 MB

People in the News profiles the lives and careers of some of today's most prominent newsmakers. Whether covering contributions and achievements or notorious deeds, books in this series examine why these well-known individuals garnered public attention.

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