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Author Andy Liaw

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Publisher Correction: A mass spectrometry-based proteome map of drug action in lung cancer cell lines.

Benjamin Ruprecht, Julie Di Bernardo, Zhao Wang, Xuan Mo, Oleg Ursu, Matthew Christopher, Rafael B Fernandez, Li Zheng, Brian D Dill, Huijun Wang, Yuting Xu, Andy Liaw, Jonathan D Mortison, Nirodhini Siriwardana, Brian Andresen, Meir Glick, James R Tata, Victoria Kutilek, Ivan Cornella-Taracido, An Chi,

An amendment to this paper has been published and can be accessed via a link at the top of the paper. ... Read more >>

Nat Chem Biol (Nature chemical biology)
[2020, 16(10):1149]

Cited: 0 times

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Nearest Neighbor Gaussian Process for Quantitative Structure-Activity Relationships.

Anthony DiFranzo, Robert P Sheridan, Andy Liaw, Matthew Tudor,

While Gaussian process models are typically restricted to smaller data sets, we propose a variation which extends its applicability to the larger data sets common in the industrial drug discovery space, making it relatively novel in the quantitative structure-activity relationship (QSAR) field. By incorporating locality-sensitive hashing for fast nearest neighbor ... Read more >>

J Chem Inf Model (Journal of chemical information and modeling)
[2020, 60(10):4653-4663]

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A mass spectrometry-based proteome map of drug action in lung cancer cell lines.

Benjamin Ruprecht, Julie Di Bernardo, Zhao Wang, Xuan Mo, Oleg Ursu, Matthew Christopher, Rafael B Fernandez, Li Zheng, Brian D Dill, Huijun Wang, Yuting Xu, Andy Liaw, Jonathan D Mortison, Nirodhini Siriwardana, Brian Andresen, Meir Glick, James R Tata, Victoria Kutilek, Ivan Cornella-Taracido, An Chi,

Mass spectrometry-based discovery proteomics is an essential tool for the proximal readout of cellular drug action. Here, we apply a robust proteomic workflow to rapidly profile the proteomes of five lung cancer cell lines in response to more than 50 drugs. Integration of millions of quantitative protein-drug associations substantially improved ... Read more >>

Nat. Chem. Biol. (Nature chemical biology)
[2020, 16(10):1111-1119]

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Deep Dive into Machine Learning Models for Protein Engineering.

Yuting Xu, Deeptak Verma, Robert P Sheridan, Andy Liaw, Junshui Ma, Nicholas M Marshall, John McIntosh, Edward C Sherer, Vladimir Svetnik, Jennifer M Johnston,

Protein redesign and engineering has become an important task in pharmaceutical research and development. Recent advances in technology have enabled efficient protein redesign by mimicking natural evolutionary mutation, selection, and amplification steps in the laboratory environment. For any given protein, the number of possible mutations is astronomical. It is impractical ... Read more >>

J Chem Inf Model (Journal of chemical information and modeling)
[2020, 60(6):2773-2790]

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Experimental Error, Kurtosis, Activity Cliffs, and Methodology: What Limits the Predictivity of Quantitative Structure-Activity Relationship Models?

Robert P Sheridan, Prabha Karnachi, Matthew Tudor, Yuting Xu, Andy Liaw, Falgun Shah, Alan C Cheng, Elizabeth Joshi, Meir Glick, Juan Alvarez,

Given a particular descriptor/method combination, some quantitative structure-activity relationship (QSAR) datasets are very predictive by random-split cross-validation while others are not. Recent literature in modelability suggests that the limiting issue for predictivity is in the data, not the QSAR methodology, and the limits are due to activity cliffs. Here, we ... Read more >>

J Chem Inf Model (Journal of chemical information and modeling)
[2020, 60(4):1969-1982]

Cited: 1 time

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Correction to Extreme Gradient Boosting as a Method for Quantitative Structure-Activity Relationships.

Robert P Sheridan, Min Wang, Andy Liaw, Junshi Ma, Eric Gifford,

J Chem Inf Model (Journal of chemical information and modeling)
[2020, 60(3):1910]

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Live Cell Membranome cDNA Screen: A Novel Homogenous Live Cell Binding Assay to Study Membrane Protein-Ligand Interaction.

Xun Shen, Elizabeth Smith, Xi Ai, William T McElroy, Andy Liaw, Tony Kreamer, Meiping Chang, Kristine Devito, Edward Hudak, Serena Xu, Yi Pei, Sylvie Sur, Andrea Peier, Jing Li,

Interactions between transmembrane receptors and their ligands play important roles in normal biological processes and pathological conditions. However, the binding partners for many transmembrane-like proteins remain elusive. To identify potential ligands of these orphan receptors, we developed a screening platform using a homogenous nonwash binding assay in live cells. A ... Read more >>

SLAS Discov (SLAS discovery : advancing life sciences R & D)
[2019, 24(10):978-986]

Cited: 0 times

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Can Galactose Be Converted to Glucose in HepG2 Cells? Improving the in Vitro Mitochondrial Toxicity Assay for the Assessment of Drug Induced Liver Injury.

Qiuwei Xu, Liping Liu, Heather Vu, Matthew Kuhls, Amy G Aslamkhan, Andy Liaw, Yan Yu, Allen Kaczor, Michael Ruth, Christina Wei, John Imredy, Jose Lebron, Kara Pearson, Raymond Gonzalez, Kaushik Mitra, Frank D Sistare,

Human hepatocellular carcinoma cells, HepG2, are often used for drug mediated mitochondrial toxicity assessments. Glucose in HepG2 culture media is replaced by galactose to reveal drug-induced mitochondrial toxicity as a marked shift of drug IC50 values for the reduction of cellular ATP. It has been postulated that galactose sensitizes HepG2 ... Read more >>

Chem Res Toxicol (Chemical research in toxicology)
[2019, 32(8):1528-1544]

Cited: 0 times

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Building Quantitative Structure-Activity Relationship Models Using Bayesian Additive Regression Trees.

Dai Feng, Vladimir Svetnik, Andy Liaw, Matthew Pratola, Robert P Sheridan,

Quantitative structure-activity relationship (QSAR) is a very commonly used technique for predicting the biological activity of a molecule using information contained in the molecular descriptors. The large number of compounds and descriptors and the sparseness of descriptors pose important challenges to traditional statistical methods and machine learning (ML) algorithms (such ... Read more >>

J Chem Inf Model (Journal of chemical information and modeling)
[2019, 59(6):2642-2655]

Cited: 2 times

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Demystifying Multitask Deep Neural Networks for Quantitative Structure-Activity Relationships.

Yuting Xu, Junshui Ma, Andy Liaw, Robert P Sheridan, Vladimir Svetnik,

Deep neural networks (DNNs) are complex computational models that have found great success in many artificial intelligence applications, such as computer vision1,2 and natural language processing.3,4 In the past four years, DNNs have also generated promising results for quantitative structure-activity relationship (QSAR) tasks.5,6 Previous work showed that DNNs can routinely ... Read more >>

J Chem Inf Model (Journal of chemical information and modeling)
[2017, 57(10):2490-2504]

Cited: 13 times

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siRNA-mediated inhibition of SREBP cleavage-activating protein reduces dyslipidemia in spontaneously dysmetabolic rhesus monkeys.

Beth Ann Murphy, Marija Tadin-Strapps, Kristian Jensen, Robin Mogg, Andy Liaw, Kithsiri Herath, Gowri Bhat, David G McLaren, Stephen F Previs, Shirly Pinto,

SREBP cleavage-activating protein (SCAP) is a cholesterol binding endoplasmic reticulum (ER) membrane protein that is required to activate SREBP transcription factors. SREBPs regulate genes involved in lipid biosynthesis. They also influence lipid clearance by modulating the expression of LDL receptor (LDLR) and proprotein convertase subtilisin/kexin type 9 (PCSK9) genes. Inhibiting ... Read more >>

Metab. Clin. Exp. (Metabolism: clinical and experimental)
[2017, 71:202-212]

Cited: 1 time

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Extreme Gradient Boosting as a Method for Quantitative Structure-Activity Relationships.

Robert P Sheridan, Wei Min Wang, Andy Liaw, Junshui Ma, Eric M Gifford,

In the pharmaceutical industry it is common to generate many QSAR models from training sets containing a large number of molecules and a large number of descriptors. The best QSAR methods are those that can generate the most accurate predictions but that are not overly expensive computationally. In this paper ... Read more >>

J Chem Inf Model (Journal of chemical information and modeling)
[2016, 56(12):2353-2360]

Cited: 22 times

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Evaluation of cynomolgus monkeys for the identification of endogenous biomarkers for hepatic transporter inhibition and as a translatable model to predict pharmacokinetic interactions with statins in humans.

Xiaoyan Chu, Shian-Jiun Shih, Rachel Shaw, Hannes Hentze, Grace H Chan, Karen Owens, Shubing Wang, Xiaoxin Cai, Deborah Newton, Jose Castro-Perez, Gino Salituro, Jairam Palamanda, Aaron Fernandis, Choon Keow Ng, Andy Liaw, Mary J Savage, Raymond Evers,

Inhibition of hepatic transporters such as organic anion transporting polypeptides (OATPs) 1B can cause drug-drug interactions (DDIs). Determining the impact of perpetrator drugs on the plasma exposure of endogenous substrates for OATP1B could be valuable to assess the risk for DDIs early in drug development. As OATP1B orthologs are well ... Read more >>

Drug Metab. Dispos. (Drug metabolism and disposition: the biological fate of chemicals)
[2015, 43(6):851-863]

Cited: 22 times

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Deep neural nets as a method for quantitative structure-activity relationships.

Junshui Ma, Robert P Sheridan, Andy Liaw, George E Dahl, Vladimir Svetnik,

Neural networks were widely used for quantitative structure-activity relationships (QSAR) in the 1990s. Because of various practical issues (e.g., slow on large problems, difficult to train, prone to overfitting, etc.), they were superseded by more robust methods like support vector machine (SVM) and random forest (RF), which arose in the ... Read more >>

J Chem Inf Model (Journal of chemical information and modeling)
[2015, 55(2):263-274]

Cited: 120 times

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Evaluation of early biomarkers of muscle anabolic response to testosterone.

Fabian Chen, Raymond Lam, David Shaywitz, Ronald C Hendrickson, Gregory J Opiteck, Dana Wishengrad, Andy Liaw, Qinghua Song, Adrian J Stewart, Corinne E Cummings, Chan Beals, Kevin E Yarasheski, Alise Reicin, Marcella Ruddy, Xuguang Hu, Nathan A Yates, Joseph Menetski, Gary A Herman,

BACKGROUND: Early biomarkers of skeletal muscle anabolism will facilitate the development of therapies for sarcopenia and frailty. METHODS AND RESULTS: We examined plasma type III collagen N-terminal propeptide (P3NP), skeletal muscle protein fractional synthesis rate, and gene and protein expression profiles to identify testosterone-induced changes in muscle anabolism. Two placebo-controlled ... Read more >>

J Cachexia Sarcopenia Muscle (Journal of cachexia, sarcopenia and muscle)
[2011, 2(1):45-56]

Cited: 13 times

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Potential biomarkers of muscle injury after eccentric exercise.

Kathy E Sietsema, Fanyu Meng, Nathan A Yates, Ronald C Hendrickson, Andy Liaw, Qinghua Song, Eric P Brass, Roger G Ulrich,

Proteomics was utilized to identify novel potential plasma biomarkers of exercise-induced muscle injury. Muscle injury was induced in nine human volunteers by eccentric upper extremity exercise. Liquid chromatography-mass spectrometry identified 30 peptides derived from nine proteins which showed significant change in abundance post-exercise. Four of these proteins, haemoglobin alpha chain, ... Read more >>

Biomarkers (Biomarkers : biochemical indicators of exposure, response, and susceptibility to chemicals)
[2010, 15(3):249-258]

Cited: 11 times

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Application of an end-to-end biomarker discovery platform to identify target engagement markers in cerebrospinal fluid by high resolution differential mass spectrometry.

Cloud P Paweletz, Matthew C Wiener, Andrey Y Bondarenko, Nathan A Yates, Qinghua Song, Andy Liaw, Anita Y H Lee, Brandon T Hunt, Ernst S Henle, Fanyu Meng, Holly Funk Sleph, Marie Holahan, Sethu Sankaranarayanan, Adam J Simon, Robert E Settlage, Jeffrey R Sachs, Mark Shearman, Alan B Sachs, Jacquelynn J Cook, Ronald C Hendrickson,

The rapid identification of protein biomarkers in biofluids is important to drug discovery and development. Here, we describe a general proteomic approach for the discovery and identification of proteins that exhibit a statistically significant difference in abundance in cerebrospinal fluid (CSF) before and after pharmacological intervention. This approach, differential mass ... Read more >>

J. Proteome Res. (Journal of proteome research)
[2010, 9(3):1392-1401]

Cited: 30 times

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Differential mass spectrometry of rat plasma reveals proteins that are responsive to 17beta-estradiol and a selective estrogen receptor modulator PPT.

Xuemei Zhao, Ekaterina G Deyanova, Laura S Lubbers, Pete Zafian, Jenny J Li, Andy Liaw, Qinghua Song, Yi Du, Robert E Settlage, Gerry J Hickey, Nathan A Yates, Ronald C Hendrickson,

Estrogens are a class of steroid hormones that interact with two related but distinct nuclear receptors, estrogen receptor (ER) alpha and beta. To identify potential ER biomarkers, we profiled the rat plasma glycoproteome after treatment with vehicle or 17beta-estradiol (E2) or an ERalpha-selective agonist PPT by differential mass spectrometry. Our ... Read more >>

J. Proteome Res. (Journal of proteome research)
[2008, 7(10):4373-4383]

Cited: 5 times

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Boosting: an ensemble learning tool for compound classification and QSAR modeling.

Vladimir Svetnik, Ting Wang, Christopher Tong, Andy Liaw, Robert P Sheridan, Qinghua Song,

A classification and regression tool, J. H. Friedman's Stochastic Gradient Boosting (SGB), is applied to predicting a compound's quantitative or categorical biological activity based on a quantitative description of the compound's molecular structure. Stochastic Gradient Boosting is a procedure for building a sequence of models, for instance regression trees (as ... Read more >>

J Chem Inf Model (Journal of chemical information and modeling)
[2005, 45(3):786-799]

Cited: 28 times

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Statistical and graphical methods for quality control determination of high-throughput screening data.

Bert Gunter, Christine Brideau, Bill Pikounis, Andy Liaw,

High-throughput screening (HTS) is used in modern drug discovery to screen hundreds of thousands to millions of compounds on selected protein targets. It is an industrial-scale process relying on sophisticated automation and state-of-the-art detection technologies. Quality control (QC) is an integral part of the process and is used to ensure ... Read more >>

J Biomol Screen (Journal of biomolecular screening)
[2003, 8(6):624-633]

Cited: 29 times

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Random forest: a classification and regression tool for compound classification and QSAR modeling.

Vladimir Svetnik, Andy Liaw, Christopher Tong, J Christopher Culberson, Robert P Sheridan, Bradley P Feuston,

A new classification and regression tool, Random Forest, is introduced and investigated for predicting a compound's quantitative or categorical biological activity based on a quantitative description of the compound's molecular structure. Random Forest is an ensemble of unpruned classification or regression trees created by using bootstrap samples of the training ... Read more >>

J Chem Inf Comput Sci (Journal of chemical information and computer sciences)
[2003, 43(6):1947-1958]

Cited: 374 times

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Improved statistical methods for hit selection in high-throughput screening.

Christine Brideau, Bert Gunter, Bill Pikounis, Andy Liaw,

High-throughput screening (HTS) plays a central role in modern drug discovery, allowing the rapid screening of large compound collections against a variety of putative drug targets. HTS is an industrial-scale process, relying on sophisticated automation, control, and state-of-the art detection technologies to organize, test, and measure hundreds of thousands to ... Read more >>

J Biomol Screen (Journal of biomolecular screening)
[2003, 8(6):634-647]

Cited: 155 times

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