Literature DB >> 28172359

CIIPro: a new read-across portal to fill data gaps using public large-scale chemical and biological data.

Daniel P Russo1, Marlene T Kim1,2, Wenyi Wang1, Daniel Pinolini1, Sunil Shende1,3, Judy Strickland4, Thomas Hartung5,6, Hao Zhu1,2.   

Abstract

Summary: We have developed a public Chemical In vitro–In vivo Profiling (CIIPro) portal, which can automatically extract in vitro biological data from public resources (i.e. PubChem) for user-supplied compounds. For compounds with in vivo target activity data (e.g. animal toxicity testing results), the integrated cheminformatics algorithm will optimize the extracted biological data using in vitro–in vivo correlations. The resulting in vitro biological data for target compounds can be used for read-across risk assessment of target compounds. Additionally, the CIIPro portal can identify the most similar compounds based on their optimized bioprofiles. The CIIPro portal provides new powerful assessment capabilities to the scientific community and can be easily integrated with other cheminformatics tools. Availability and Implementation: ciipro.rutgers.edu. Contact: danrusso@scarletmail.rutgers.edu or hao.zhu99@rutgers.edu

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Year:  2017        PMID: 28172359      PMCID: PMC6075082          DOI: 10.1093/bioinformatics/btw640

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  11 in total

1.  Read-across approaches--misconceptions, promises and challenges ahead.

Authors:  Grace Patlewicz; Nicholas Ball; Richard A Becker; Ewan D Booth; Mark T D Cronin; Dinant Kroese; David Steup; Ben van Ravenzwaay; Thomas Hartung
Journal:  ALTEX       Date:  2014       Impact factor: 6.043

2.  Predictive Modeling of Estrogen Receptor Binding Agents Using Advanced Cheminformatics Tools and Massive Public Data.

Authors:  Kathryn Ribay; Marlene T Kim; Wenyi Wang; Daniel Pinolini; Hao Zhu
Journal:  Front Environ Sci       Date:  2016-03-08

3.  Developing Enhanced Blood-Brain Barrier Permeability Models: Integrating External Bio-Assay Data in QSAR Modeling.

Authors:  Wenyi Wang; Marlene T Kim; Alexander Sedykh; Hao Zhu
Journal:  Pharm Res       Date:  2015-04-11       Impact factor: 4.200

4.  A novel two-step hierarchical quantitative structure-activity relationship modeling work flow for predicting acute toxicity of chemicals in rodents.

Authors:  Hao Zhu; Lin Ye; Ann Richard; Alexander Golbraikh; Fred A Wright; Ivan Rusyn; Alexander Tropsha
Journal:  Environ Health Perspect       Date:  2009-04-03       Impact factor: 9.031

5.  Critical evaluation of human oral bioavailability for pharmaceutical drugs by using various cheminformatics approaches.

Authors:  Marlene T Kim; Alexander Sedykh; Suman K Chakravarti; Roustem D Saiakhov; Hao Zhu
Journal:  Pharm Res       Date:  2013-12-03       Impact factor: 4.200

6.  Integrative chemical-biological read-across approach for chemical hazard classification.

Authors:  Yen Low; Alexander Sedykh; Denis Fourches; Alexander Golbraikh; Maurice Whelan; Ivan Rusyn; Alexander Tropsha
Journal:  Chem Res Toxicol       Date:  2013-08-05       Impact factor: 3.739

7.  Supporting read-across using biological data.

Authors:  Hao Zhu; Mounir Bouhifd; Elizabeth Donley; Laura Egnash; Nicole Kleinstreuer; E Dinant Kroese; Zhichao Liu; Thomas Luechtefeld; Jessica Palmer; David Pamies; Jie Shen; Volker Strauss; Shengde Wu; Thomas Hartung
Journal:  ALTEX       Date:  2016-02-11       Impact factor: 6.043

8.  Toward Good Read-Across Practice (GRAP) guidance.

Authors:  Nicholas Ball; Mark T D Cronin; Jie Shen; Karen Blackburn; Ewan D Booth; Mounir Bouhifd; Elizabeth Donley; Laura Egnash; Charles Hastings; Daland R Juberg; Andre Kleensang; Nicole Kleinstreuer; E Dinant Kroese; Adam C Lee; Thomas Luechtefeld; Alexandra Maertens; Sue Marty; Jorge M Naciff; Jessica Palmer; David Pamies; Mike Penman; Andrea-Nicole Richarz; Daniel P Russo; Sharon B Stuard; Grace Patlewicz; Bennard van Ravenzwaay; Shengde Wu; Hao Zhu; Thomas Hartung
Journal:  ALTEX       Date:  2016-02-11       Impact factor: 6.043

Review 9.  Big data in chemical toxicity research: the use of high-throughput screening assays to identify potential toxicants.

Authors:  Hao Zhu; Jun Zhang; Marlene T Kim; Abena Boison; Alexander Sedykh; Kimberlee Moran
Journal:  Chem Res Toxicol       Date:  2014-09-16       Impact factor: 3.739

10.  Mechanism Profiling of Hepatotoxicity Caused by Oxidative Stress Using Antioxidant Response Element Reporter Gene Assay Models and Big Data.

Authors:  Marlene Thai Kim; Ruili Huang; Alexander Sedykh; Wenyi Wang; Menghang Xia; Hao Zhu
Journal:  Environ Health Perspect       Date:  2015-09-18       Impact factor: 9.031

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  15 in total

1.  Mechanism-Driven Read-Across of Chemical Hepatotoxicants Based on Chemical Structures and Biological Data.

Authors:  Linlin Zhao; Daniel P Russo; Wenyi Wang; Lauren M Aleksunes; Hao Zhu
Journal:  Toxicol Sci       Date:  2020-04-01       Impact factor: 4.849

Review 2.  Advancing computer-aided drug discovery (CADD) by big data and data-driven machine learning modeling.

Authors:  Linlin Zhao; Heather L Ciallella; Lauren M Aleksunes; Hao Zhu
Journal:  Drug Discov Today       Date:  2020-07-11       Impact factor: 7.851

Review 3.  Big-data and machine learning to revamp computational toxicology and its use in risk assessment.

Authors:  Thomas Luechtefeld; Craig Rowlands; Thomas Hartung
Journal:  Toxicol Res (Camb)       Date:  2018-05-01       Impact factor: 3.524

4.  Navigating through the minefield of read-across tools: A review of in silico tools for grouping.

Authors:  Patlewicz Grace; Helman George; Pradeep Prachi; Shah Imran
Journal:  Comput Toxicol       Date:  2017-08

5.  Multi-Descriptor Read Across (MuDRA): A Simple and Transparent Approach for Developing Accurate Quantitative Structure-Activity Relationship Models.

Authors:  Vinicius M Alves; Alexander Golbraikh; Stephen J Capuzzi; Kammy Liu; Wai In Lam; Daniel Robert Korn; Diane Pozefsky; Carolina Horta Andrade; Eugene N Muratov; Alexander Tropsha
Journal:  J Chem Inf Model       Date:  2018-06-13       Impact factor: 4.956

6.  Exploring current read-across applications and needs among selected U.S. Federal Agencies.

Authors:  Grace Patlewicz; Lucina E Lizarraga; Diego Rua; David G Allen; Amber B Daniel; Suzanne C Fitzpatrick; Natàlia Garcia-Reyero; John Gordon; Pertti Hakkinen; Angela S Howard; Agnes Karmaus; Joanna Matheson; Moiz Mumtaz; Andrea-Nicole Richarz; Patricia Ruiz; Louis Scarano; Takashi Yamada; Nicole Kleinstreuer
Journal:  Regul Toxicol Pharmacol       Date:  2019-05-10       Impact factor: 3.271

Review 7.  Big Data and Artificial Intelligence Modeling for Drug Discovery.

Authors:  Hao Zhu
Journal:  Annu Rev Pharmacol Toxicol       Date:  2019-09-13       Impact factor: 13.820

8.  Comparing Multiple Machine Learning Algorithms and Metrics for Estrogen Receptor Binding Prediction.

Authors:  Daniel P Russo; Kimberley M Zorn; Alex M Clark; Hao Zhu; Sean Ekins
Journal:  Mol Pharm       Date:  2018-08-28       Impact factor: 4.939

9.  High-Throughput Screening Assay Profiling for Large Chemical Databases.

Authors:  Daniel P Russo; Hao Zhu
Journal:  Methods Mol Biol       Date:  2022

10.  Construction of a Virtual Opioid Bioprofile: A Data-Driven QSAR Modeling Study to Identify New Analgesic Opioids.

Authors:  Xuelian Jia; Heather L Ciallella; Daniel P Russo; Linlin Zhao; Morgan H James; Hao Zhu
Journal:  ACS Sustain Chem Eng       Date:  2021-03-04       Impact factor: 8.198

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