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381 results on '"Nikolsky, Yuri"'

1. Increasing Papers' Discoverability with Precise Semantic Labeling: the sci.AI Platform

Author

Gurinovich, Roman, Pashuk, Alexander, Petrovskiy, Yuriy, Dmitrievskij, Alex, Kuryan, Oleg, Scerbacov, Alexei, Tiggre, Antonia, Moroz, Elena, and Nikolsky, Yuri

Subjects
Computer Science - Information Retrieval, Computer Science - Computation and Language
Abstract

The number of published findings in biomedicine increases continually. At the same time, specifics of the domain's terminology complicates the task of relevant publications retrieval. In the current research, we investigate influence of terms' variability and ambiguity on a paper's likelihood of being retrieved. We obtained statistics that demonstrate significance of the issue and its challenges, followed by presenting the sci.AI platform, which allows precise terms labeling as a resolution.

Published
2017

2. GrantMed: a new, international system for tracking grants and funding trends in the life sciences

Author

Nikolsky, Yuri, Gurinovich, Roman, Kuryan, Oleg, Pashuk, Aleksandr, Scherbakov, Alexej, Romantsov, Konstantin, Jellen, Leslie C., and Zhavoronkov, Alex

Subjects
Computer Science - Digital Libraries, Computer Science - Databases, Computer Science - Information Retrieval
Abstract

Despite the success of PubMed and other search engines in managing the massive volume of biomedical literature and the retrieval of individual publications, grant-related data remains scattered and relatively inaccessible. This is problematic, as project and funding data has significant analytical value and could be integral to publication retrieval. Here, we introduce GrantMed, a searchable international database of biomedical grants that integrates some 20 million publications with the nearly 1.4 million research projects and 650 billion dollars of funding that made them possible. For any given topic in the life sciences, Grantmed provides instantaneous visualization of the past 30 years of dollars spent and projects awarded, along with detailed individual project descriptions, funding amounts, and links to investigators, research organizations, and resulting publications. It summarizes trends in funding and publication rates for areas of interest and merges data from various national grant databases to create one international grant tracking system. This information will benefit the research community and funding entities alike. Users can view trends over time or current projects underway and use this information to navigate the decision-making process in moving forward. They can view projects prior to publication and records of previous projects. Convenient access to this data for analytical purposes will be beneficial in many ways, helping to prevent project overlap, reduce funding redundancy, identify areas of success, accelerate dissemination of ideas, and expose knowledge gaps in moving forward. It is our hope that this will be a central resource for international life sciences research communities and the funding organizations that support them, ultimately streamlining progress.

Published
2015

3. Whole-genome modeling accurately predicts quantitative traits in plants

Author

Gentzbittel, Laurent, Ben, Cecile, Mazurier, Melanie, Shin, Min-Gyoung, Triska, Martin, Rickauer, Martina, Nikolsky, Yuri, Marjoram, Paul, Nuzhdin, Sergey, and Tatarinova, Tatiana

Subjects
Quantitative Biology - Populations and Evolution
Abstract

Understanding the relationship between genomic variation and variation in phenotypes for quantitative traits such as physiology, yield, fitness or behavior, will provide important insights for both predicting adaptive evolution and for breeding schemes. A particular question is whether the genetic variation that influences quantitative phenotypes is typically the result of one or two mutations of large effect, or multiple mutations of small effect. In this paper we explore this issue using the wild model legume Medicago truncatula. We show that phenotypes, such as quantitative disease resistance, can be well-predicted using genome-wide patterns of admixture, from which it follows that there must be many mutations of small effect. Our findings prove the potential of our novel 'whole-genome modeling' -WhoGEM- method and experimentally validate, for the first time, the infinitesimal model as a mechanism for adaptation of quantitative phenotypes in plants. This insight can accelerate breeding and biomedicine research programs.

Published
2015

4. The mysterious orphans of Mycoplasmataceae

Author

Tatarinova, Tatiana V., Lysnyansky, Inna, Nikolsky, Yuri V., and Bolshoy, Alexander

Subjects
Quantitative Biology - Genomics
Abstract

Background: The length of a protein sequence is largely determined by its function, i.e. each functional group is associated with an optimal size. However, comparative genomics revealed that proteins length may be affected by additional factors. In 2002 it was shown that in bacterium Escherichia coli and the archaeon Archaeoglobus fulgidus, protein sequences with no homologs are, on average, shorter than those with homologs. Most experts now agree that the length distributions are distinctly different between protein sequences with and without homologs in bacterial and archaeal genomes. In this study, we examine this postulate by a comprehensive analysis of all annotated prokaryotic genomes and focusing on certain exceptions. Results: We compared lengths distributions of having homologs proteins (HHPs) and non-having homologs proteins (orphans or ORFans) in all currently annotated completely sequenced prokaryotic genomes. As expected, the HHPs and ORFans have strikingly different length distributions in almost all genomes. As previously established, the HHPs, indeed, are, on average, longer than the ORFans, and the length distributions for the ORFans have a relatively narrow peak, in contrast to the HHPs, whose lengths spread over a wider range of values. However, about thirty genomes do not obey these rules. Practically all genomes of Mycoplasma and Ureaplasma have atypical ORFans distributions, with the mean lengths of ORFan larger than the mean lengths of HHPs. These genera constitute over 80% of atypical genomes. Conclusions: We confirmed on a ubiquitous set of genomes the previous observation that HHPs and ORFans have different gene length distributions. We also showed that Mycoplasmataceae genomes have distinctive distributions of ORFans lengths. We offer several possible biological explanations of this phenomenon.

Published
2015

5. Genomic study of the Ket: a Paleo-Eskimo-related ethnic group with significant ancient North Eurasian ancestry

Author

Flegontov, Pavel, Changmai, Piya, Zidkova, Anastassiya, Logacheva, Maria D., Flegontova, Olga, Gelfand, Mikhail S., Gerasimov, Evgeny S., Khrameeva, Ekaterina E., Konovalova, Olga P., Neretina, Tatiana, Nikolsky, Yuri V., Starostin, George, Stepanova, Vita V., Travinsky, Igor V., Tříska, Martin, Tříska, Petr, and Tatarinova, Tatiana V.

Subjects
Quantitative Biology - Populations and Evolution
Abstract

The Kets, an ethnic group in the Yenisei River basin, Russia, are considered the last nomadic hunter-gatherers of Siberia, and Ket language has no transparent affiliation with any language family. We investigated connections between the Kets and Siberian and North American populations, with emphasis on the Mal'ta and Paleo-Eskimo ancient genomes using original data from 46 unrelated samples of Kets and 42 samples of their neighboring ethnic groups (Uralic-speaking Nganasans, Enets, and Selkups). We genotyped over 130,000 autosomal SNPs, determined mitochondrial and Y-chromosomal haplogroups, and performed high-coverage genome sequencing of two Ket individuals. We established that the Kets belong to the cluster of Siberian populations related to Paleo-Eskimos. Unlike other members of this cluster (Nganasans, Ulchi, Yukaghirs, and Evens), Kets and closely related Selkups have a high degree of Mal'ta ancestry. Implications of these findings for the linguistic hypothesis uniting Ket and Na-Dene languages into a language macrofamily are discussed.

Published
2015

6. Table S1 from Spatial Proximity to Fibroblasts Impacts Molecular Features and Therapeutic Sensitivity of Breast Cancer Cells Influencing Clinical Outcomes

Author

Marusyk, Andriy, primary, Tabassum, Doris P., primary, Janiszewska, Michalina, primary, Place, Andrew E., primary, Trinh, Anne, primary, Rozhok, Andrii I., primary, Pyne, Saumyadipta, primary, Guerriero, Jennifer L., primary, Shu, Shaokun, primary, Ekram, Muhammad, primary, Ishkin, Alexander, primary, Cahill, Daniel P., primary, Nikolsky, Yuri, primary, Chan, Timothy A., primary, Rimawi, Mothaffar F., primary, Hilsenbeck, Susan, primary, Schiff, Rachel, primary, Osborne, Kent C., primary, Letai, Antony, primary, and Polyak, Kornelia, primary

Published
2023
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7. Supplementary Data from Spatial Proximity to Fibroblasts Impacts Molecular Features and Therapeutic Sensitivity of Breast Cancer Cells Influencing Clinical Outcomes

Author

Marusyk, Andriy, primary, Tabassum, Doris P., primary, Janiszewska, Michalina, primary, Place, Andrew E., primary, Trinh, Anne, primary, Rozhok, Andrii I., primary, Pyne, Saumyadipta, primary, Guerriero, Jennifer L., primary, Shu, Shaokun, primary, Ekram, Muhammad, primary, Ishkin, Alexander, primary, Cahill, Daniel P., primary, Nikolsky, Yuri, primary, Chan, Timothy A., primary, Rimawi, Mothaffar F., primary, Hilsenbeck, Susan, primary, Schiff, Rachel, primary, Osborne, Kent C., primary, Letai, Antony, primary, and Polyak, Kornelia, primary

Published
2023
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8. Data from Spatial Proximity to Fibroblasts Impacts Molecular Features and Therapeutic Sensitivity of Breast Cancer Cells Influencing Clinical Outcomes

Author

Marusyk, Andriy, primary, Tabassum, Doris P., primary, Janiszewska, Michalina, primary, Place, Andrew E., primary, Trinh, Anne, primary, Rozhok, Andrii I., primary, Pyne, Saumyadipta, primary, Guerriero, Jennifer L., primary, Shu, Shaokun, primary, Ekram, Muhammad, primary, Ishkin, Alexander, primary, Cahill, Daniel P., primary, Nikolsky, Yuri, primary, Chan, Timothy A., primary, Rimawi, Mothaffar F., primary, Hilsenbeck, Susan, primary, Schiff, Rachel, primary, Osborne, Kent C., primary, Letai, Antony, primary, and Polyak, Kornelia, primary

Published
2023
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11. Supplementary File 3 from Genome-Wide Functional Synergy between Amplified and Mutated Genes in Human Breast Cancer

Author

Nikolsky, Yuri, primary, Sviridov, Evgeny, primary, Yao, Jun, primary, Dosymbekov, Damir, primary, Ustyansky, Vadim, primary, Kaznacheev, Valery, primary, Dezso, Zoltan, primary, Mulvey, Laura, primary, Macconaill, Laura E., primary, Winckler, Wendy, primary, Serebryiskaya, Tatiana, primary, Nikolskaya, Tatiana, primary, and Polyak, Kornelia, primary

Published
2023
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12. Supplementary File 2 from Genome-Wide Functional Synergy between Amplified and Mutated Genes in Human Breast Cancer

Author

Nikolsky, Yuri, primary, Sviridov, Evgeny, primary, Yao, Jun, primary, Dosymbekov, Damir, primary, Ustyansky, Vadim, primary, Kaznacheev, Valery, primary, Dezso, Zoltan, primary, Mulvey, Laura, primary, Macconaill, Laura E., primary, Winckler, Wendy, primary, Serebryiskaya, Tatiana, primary, Nikolskaya, Tatiana, primary, and Polyak, Kornelia, primary

Published
2023
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13. Supplementary File 1 from Genome-Wide Functional Synergy between Amplified and Mutated Genes in Human Breast Cancer

Author

Nikolsky, Yuri, primary, Sviridov, Evgeny, primary, Yao, Jun, primary, Dosymbekov, Damir, primary, Ustyansky, Vadim, primary, Kaznacheev, Valery, primary, Dezso, Zoltan, primary, Mulvey, Laura, primary, Macconaill, Laura E., primary, Winckler, Wendy, primary, Serebryiskaya, Tatiana, primary, Nikolskaya, Tatiana, primary, and Polyak, Kornelia, primary

Published
2023
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15. Supplementary File 5 from Genome-Wide Functional Synergy between Amplified and Mutated Genes in Human Breast Cancer

Author

Nikolsky, Yuri, primary, Sviridov, Evgeny, primary, Yao, Jun, primary, Dosymbekov, Damir, primary, Ustyansky, Vadim, primary, Kaznacheev, Valery, primary, Dezso, Zoltan, primary, Mulvey, Laura, primary, Macconaill, Laura E., primary, Winckler, Wendy, primary, Serebryiskaya, Tatiana, primary, Nikolskaya, Tatiana, primary, and Polyak, Kornelia, primary

Published
2023
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17. Supplementary File 4 from Genome-Wide Functional Synergy between Amplified and Mutated Genes in Human Breast Cancer

Author

Nikolsky, Yuri, primary, Sviridov, Evgeny, primary, Yao, Jun, primary, Dosymbekov, Damir, primary, Ustyansky, Vadim, primary, Kaznacheev, Valery, primary, Dezso, Zoltan, primary, Mulvey, Laura, primary, Macconaill, Laura E., primary, Winckler, Wendy, primary, Serebryiskaya, Tatiana, primary, Nikolskaya, Tatiana, primary, and Polyak, Kornelia, primary

Published
2023
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28. Supplementary File 6 from Genome-Wide Functional Synergy between Amplified and Mutated Genes in Human Breast Cancer

Author

Nikolsky, Yuri, primary, Sviridov, Evgeny, primary, Yao, Jun, primary, Dosymbekov, Damir, primary, Ustyansky, Vadim, primary, Kaznacheev, Valery, primary, Dezso, Zoltan, primary, Mulvey, Laura, primary, Macconaill, Laura E., primary, Winckler, Wendy, primary, Serebryiskaya, Tatiana, primary, Nikolskaya, Tatiana, primary, and Polyak, Kornelia, primary

Published
2023
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29. Materials and Methods, Legends, Tables and Figures from Genome-Wide Functional Synergy between Amplified and Mutated Genes in Human Breast Cancer

Author

Nikolsky, Yuri, primary, Sviridov, Evgeny, primary, Yao, Jun, primary, Dosymbekov, Damir, primary, Ustyansky, Vadim, primary, Kaznacheev, Valery, primary, Dezso, Zoltan, primary, Mulvey, Laura, primary, Macconaill, Laura E., primary, Winckler, Wendy, primary, Serebryiskaya, Tatiana, primary, Nikolskaya, Tatiana, primary, and Polyak, Kornelia, primary

Published
2023
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36. Altered antisense-to-sense transcript ratios in breast cancer

Author

Maruyama, Reo, Shipitsin, Michail, Choudhury, Sibgat, Wu, Zhenhua, Protopopov, Alexei, Yao, Jun, Lo, Pang-Kuo, Bessarabova, Marina, Ishkin, Alex, Nikolsky, Yuri, Liu, X. Shirley, Sukumar, Saraswati, and Polyak, Kornelia

Published
2012

37. The Genetic Landscape of the Childhood Cancer Medulloblastoma

Author

Parsons, D. Williams, Li, Meng, Zhang, Xiaosong, Jones, Siân, Leary, Rebecca J., Lin, Jimmy Cheng-Ho, Boca, Simina M., Carter, Hannah, Samayoa, Josue, Bettegowda, Chetan, Gallia, Gary L., Jallo, George I., Binder, Zev A., Nikolsky, Yuri, Hartigan, James, Smith, Doug R., Gerhard, Daniela S., Fults, Daniel W., VandenBerg, Scott, Berger, Mitchel S., Marie, Suely Kazue Nagahashi, Shinjo, Sueli Mieko Oba, Clara, Carlos, Phillips, Peter C., Minturn, Jane E., Biegel, Jaclyn A., Judkins, Alexander R., Resnick, Adam C., Storm, Phillip B., Curran, Tom, He, Yiping, Rasheed, B. Ahmed, Friedman, Henry S., Keir, Stephen T., McLendon, Roger, Northcott, Paul A., Taylor, Michael D., Burger, Peter C., Riggins, Gregory J., Karchin, Rachel, Parmigiani, Giovanni, Bigner, Darell D., Yan, Hai, Papadopoulos, Nick, Vogelstein, Bert, Kinzler, Kenneth W., and Velculescu, Victor E.

Published
2011
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38. Integrated Analysis of Homozygous Deletions, Focal Amplifications, and Sequence Alterations in Breast and Colorectal Cancers

Author

Leary, Rebecca J., Lin, Jimmy C., Cummins, Jordan, Boca, Simina, Wood, Laura D., Parsons, D. Williams, Jones, Siân, Sjöblom, Tobias, Park, Ben-Ho, Parsons, Ramon, Willis, Joseph, Dawson, Dawn, Willson, James K. V., Nikolskaya, Tatiana, Nikolsky, Yuri, Kopelovich, Levy, Papadopoulos, Nick, Pennacchio, Len A., Wang, Tian-Li, Markowitz, Sanford D., Parmigiani, Giovanni, Kinzler, Kenneth W., Vogelstein, Bert, and Velculescu, Victor E.

Published
2008
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39. An Integrated Genomic Analysis of Human Glioblastoma Multiforme

Author

Parsons, D. Williams, Jones, Siân, Zhang, Xiaosong, Lin, Jimmy Cheng-Ho, Leary, Rebecca J., Angenendt, Philipp, Mankoo, Parminder, Carter, Hannah, Siu, I-Mei, Gallia, Gary L., Olivi, Alessandro, McLendon, Roger, Rasheed, B. Ahmed, Keir, Stephen, Nikolskaya, Tatiana, Nikolsky, Yuri, Busam, Dana A., Tekleab, Hanna, Diaz, Luis A., Hartigar, James, Smith, Doug R., Strausberg, Robert L., Marie, Suely Kazue Nagahashi, Shinjo, Sueli Mieko Oba, Yan, Hai, Riggins, Gregory J., Bigner, Darell D., Karchin, Rachel, Papadopoulos, Nick, Parmigiani, Giovanni, Vogelstein, Bert, Velculescu, Victor E., and Kinzler, Kenneth W.

Published
2008
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40. Core Signaling Pathways in Human Pancreatic Cancers Revealed by Global Genomic Analyses

Author

Jones, Siân, Zhang, Xiaosong, Parsons, D. Williams, Lin, Jimmy Cheng-Ho, Leary, Rebecca J., Angenendt, Philipp, Mankoo, Parminder, Carter, Hannah, Kamiyama, Hirohiko, Jimeno, Antonio, Hong, Seung-Mo, Fu, Baojin, Lin, Ming-Tseh, Calhoun, Eric S., Kamiyama, Mihoko, Walter, Kimberly, Nikolskaya, Tatiana, Nikolsky, Yuri, Hartigan, James, Smith, Douglas R., Hidalgo, Manuel, Leach, Steven D., Klein, Alison P., Jaffee, Elizabeth M., Goggins, Michael, Maitra, Anirban, Iacobuzio-Donahue, Christine, Eshleman, James R., Kern, Scott E., Hruban, Ralph H., Karchin, Rachel, Papadopoulos, Nickolas, Parmigiani, Giovanni, Vogelstein, Bert, Velculescu, Victor E., and Kinzler, Kenneth W.

Published
2008
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41. Cell Type-Specific DNA Methylation Patterns in the Human Breast

Author

Bloushtain-Qimron, Noga, Yao, Jun, Snyder, Eric L., Shipitsin, Michail, Campbell, Lauren L., Mani, Sendurai A., Hu, Min, Chen, Haiyan, Ustyansky, Vadim, Antosiewicz, Jessica E., Argani, Pedram, Halushka, Marc K., Thomson, James A., Pharoah, Paul, Porgador, Angel, Sukumar, Saraswati, Parsons, Ramon, Richardson, Andrea L., Stampfer, Martha R., Gelman, Rebecca S., Nikolskaya, Tatiana, Nikolsky, Yuri, and Polyak, Kornelia

Published
2008
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42. The Genomic Landscapes of Human Breast and Colorectal Cancers

Author

Wood, Laura D., Parsons, D. Williams, Jones, Siân, Lin, Jimmy, Sjöblom, Tobias, Leary, Rebecca J., Shen, Dong, Boca, Simina M., Barber, Thomas, Ptak, Janine, Silliman, Natalie, Szabo, Steve, Dezso, Zoltan, Ustyanksky, Vadim, Nikolskaya, Tatiana, Nikolsky, Yuri, Karchin, Rachel, Wilson, Paul A., Kaminker, Joshua S., Zhang, Zemin, Croshaw, Randal, Willis, Joseph, Dawson, Dawn, Shipitsin, Michail, Willson, James K. V., Sukumar, Saraswati, Polyak, Kornelia, Park, Ben Ho, Pethiyagoda, Charit L., Pant, P. V. Krishna, Ballinger, Dennis G., Sparks, Andrew B., Hartigan, James, Smith, Douglas R., Suh, Erick, Papadopoulos, Nickolas, Buckhaults, Phillip, Markowitz, Sanford D., Parmigiani, Giovanni, Kinzler, Kenneth W., Velculescu, Victor E., and Vogelstein, Bert

Published
2007
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43. Regulation of In Situ to Invasive Breast Carcinoma Transition

Author

Hu, Min, Yao, Jun, Carroll, Danielle K., Weremowicz, Stanislawa, Chen, Haiyan, Carrasco, Daniel, Richardson, Andrea, Violette, Shelia, Nikolskaya, Tatiana, Nikolsky, Yuri, Bauerlein, Erica L., Hahn, William C., Gelman, Rebecca S., Allred, Craig, Bissell, Mina J., Schnitt, Stuart, and Polyak, Kornelia

Published
2008
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44. The JAK2/STAT3 signaling pathway is required for growth of CD44+CD24-stem cell-like breast cancer cells in human tumors

Author

Marotta, Lauren L.C., Almendro, Vanessa, Marusyk, Andriy, Shipitsin, Michail, Schemme, Janina, Walker, Sarah R., Bloushtain-Qimron, Noga, Kim, Jessica J., Choudhury, Sibgat A., Maruyama, Reo, Wu, Zhenhua, Gonen, Mithat, Mulvey, Laura A., Bessarabova, Marina O., Huh, Sung Jin, Silver, Serena J., Kim, So Young, Park, So Yeon, Lee, Hee Eun, Anderson, Karen S., Richardson, Andrea L., Nikolskaya, Tatiana, Nikolsky, Yuri, Liu, X. Shirley, Root, David E., Hahn, William C., Frank, David A., and Polyak, Kornelia

Subjects
Protein kinases -- Physiological aspects -- Research, Cancer cells -- Physiological aspects -- Research -- Growth, Breast cancer -- Risk factors -- Research, Company growth, Health care industry
Abstract

Intratumor heterogeneity is a major clinical problem because tumor cell subtypes display variable sensitivity to therapeutics and may play different roles in progression. We previously characterized 2 cell populations in [...]

Published
2011
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45. Knowledge-based analysis of proteomics data

Author

Bessarabova Marina, Ishkin Alexander, JeBailey Lellean, Nikolskaya Tatiana, and Nikolsky Yuri

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Published
2012
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46. Molecular Definition of Breast Tumor Heterogeneity

Author

Shipitsin, Michail, Campbell, Lauren L., Argani, Pedram, Weremowicz, Stanislawa, Bloushtain-Qimron, Noga, Yao, Jun, Nikolskaya, Tatiana, Serebryiskaya, Tatiana, Beroukhim, Rameen, Hu, Min, Halushka, Marc K., Sukumar, Saraswati, Parker, Leroy M., Anderson, Karen S., Harris, Lyndsay N., Garber, Judy E., Richardson, Andrea L., Schnitt, Stuart J., Nikolsky, Yuri, Gelman, Rebecca S., and Polyak, Kornelia

Published
2007
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47. Bimodal gene expression patterns in breast cancer

Author

Nikolsky Yuri, Bugrim Andrej, Shi Weiwei, Kirillov Eugene, Bessarabova Marina, and Nikolskaya Tatiana

Subjects
Biotechnology, TP248.13-248.65, Genetics, QH426-470
Abstract

Abstract We identified a set of genes with an unexpected bimodal distribution among breast cancer patients in multiple studies. The property of bimodality seems to be common, as these genes were found on multiple microarray platforms and in studies with different end-points and patient cohorts. Bimodal genes tend to cluster into small groups of four to six genes with synchronised expression within the group (but not between the groups), which makes them good candidates for robust conditional descriptors. The groups tend to form concise network modules underlying their function in cancerogenesis of breast neoplasms.

Published
2010
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48. Techniques: application of systems biology to absorption, distribution, metabolism, excretion and toxicity

Author

Ekins, Sean, Nikolsky, Yuri, and Nikolskaya, Tatiana

Subjects
Algorithms -- Physiological aspects, Distribution management software -- Physiological aspects, Algorithm, Retail/distribution/wholesale software, Distribution management software, Food and beverage production/distribution software, Biological sciences, Chemistry, Pharmaceuticals and cosmetics industries
Abstract

It is widely recognized that either predicting or determining the absorption, distribution, metabolism, excretion and toxicity (ADME/Tox) properties of molecules helps to prevent the failure of some compounds before they reach the clinic. Consequently, there has been considerable research into developing better in silico, in vitro and in vivo methods and models. Toxicogenomics, proteomics, metabonomics and pharmacogenomics represent the latest experimental approaches that can be combined with high-throughput molecular screening of targets to provide a view of the complete biological system that is modulated by a compound. The functional interpretation and relevance of these complex multidimensional data to the phenotype observed in humans is the focus of current research in toxicology. Multiple content databases, data mining and predictive modeling algorithms, visualization tools, and high-throughput data-analysis solutions are being integrated to form systems-ADME/Tox. In this review, we focus on the most recent advances and applications in this area.

Published
2005

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