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Slobodan Vucetic

Slobodan Vucetic

D-Index & Metrics

Computer Science

D-Index
39
Citations
11052
World Ranking
9529
National Ranking
4038

Overview

Slobodan Vucetic is affiliated with Temple University in the United States and has contributed extensively to the field of Computer Science, with a particular focus on Artificial Intelligence. Their research spans related subfields including Genetics, Oncology, Molecular Biology, and Cognitive Neuroscience.

Their recent papers cover a range of interdisciplinary topics and were published in various academic venues. Notable publications include:

  • "The generative capacity of probabilistic protein sequence models," 2021, Nature Communications
  • "Sparse Principal Component Analysis with Constraints," 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • "Socioeconomic Disparities in Colon Cancer Survival," 2020, Epidemiology
  • "Convex Kernelized Sorting," 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • "Multifaceted analysis of training and testing convolutional neural networks for protein secondary structure prediction," 2020, PLoS ONE

Commonly explored topics in Vucetic's research include:

  • Autism Spectrum Disorder Research
  • Topic Modeling
  • Global Cancer Incidence and Screening
  • Assistive Technology in Communication and Mobility
  • Anomaly Detection Techniques and Applications
  • Biomedical Text Mining and Ontologies
  • Natural Language Processing Techniques

Frequent collaborators include Eduard Dragut, Aniruddha Maiti, Elizabeth Garrison, Daniel Wiese, and Antoinette M. Stroup.

Research outputs have been disseminated in a variety of publication venues. The most frequent include:

  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • Nature Communications
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • BMC Medical Informatics and Decision Making

Vucetic's work integrates computational methods with biomedical and cancer research, reflecting a multidisciplinary approach that bridges artificial intelligence techniques with genetics and oncology. This cross-domain expertise positions their contributions at the intersection of technology and health sciences.

Best Publications

  • A large-scale evaluation of computational protein function prediction

    Predrag Radivojac;Wyatt T Clark;Tal Ronnen Oron;Alexandra M Schnoes

  • Length-dependent prediction of protein intrinsic disorder

    Kang Peng;Predrag Radivojac;Slobodan Vucetic;A Keith Dunker

  • Functional anthology of intrinsic disorder. 1. Biological processes and functions of proteins with long disordered regions.

    Hongbo Xie;Slobodan Vucetic;Lilia M. Iakoucheva;Christopher J. Oldfield

  • Exploiting heterogeneous sequence properties improves prediction of protein disorder.

    Zoran Obradovic;Kang Peng;Slobodan Vucetic;Predrag Radivojac

  • Optimizing long intrinsic disorder predictors with protein evolutionary information.

    Kang Peng;Slobodan Vucetic;Predrag Radivojac;Celeste J. Brown

  • Predicting Intrinsic Disorder From Amino Acid Sequence

    Zoran Obradovic;Kang Peng;Slobodan Vucetic;Predrag Radivojac

  • An expanded evaluation of protein function prediction methods shows an improvement in accuracy

    Yuxiang Jiang;Tal Ronnen Oron;Wyatt T. Clark;Asma R. Bankapur

  • The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

    Naihui Zhou;Yuxiang Jiang;Timothy R. Bergquist;Alexandra J. Lee

  • Functional Anthology of Intrinsic Disorder. 3. Ligands, Post-Translational Modifications, and Diseases Associated with Intrinsically Disordered Proteins

    Hongbo Xie;Slobodan Vucetic;Lilia M. Iakoucheva;Christopher J. Oldfield

  • Functional anthology of intrinsic disorder. 2. Cellular components, domains, technical terms, developmental processes, and coding sequence diversities correlated with long disordered regions.

    Slobodan Vucetic;Hongbo Xie;Lilia M. Iakoucheva;Christopher J. Oldfield

  • Unfoldomics of human diseases: linking protein intrinsic disorder with diseases

    Vladimir N Uversky;Vladimir N Uversky;Christopher J Oldfield;Uros Midic;Hongbo Xie

  • An expanded evaluation of protein function prediction methods shows an improvement in accuracy

    Yuxiang Jiang;Tal Ronnen Oron;Wyatt T Clark;Asma R Bankapur

  • DisProt: a database of protein disorder

    Slobodan Vucetic;Zoran Obradovic;Vladimir Vacic;Predrag Radivojac

  • Breaking the curse of kernelization: budgeted stochastic gradient descent for large-scale SVM training

    Zhuang Wang;Koby Crammer;Slobodan Vucetic

  • Interpretable Representation Learning for Healthcare via Capturing Disease Progression through Time

    Tian Bai;Shanshan Zhang;Brian L. Egleston;Slobodan Vucetic

  • Collaborative Filtering Using a Regression-Based Approach

    Slobodan Vucetic;Zoran Obradovic

  • Calmodulin signaling: Analysis and prediction of a disorder-dependent molecular recognition

    Predrag Radivojac;Slobodan Vucetic;Timothy R. O'Connor;Vladimir N. Uversky

  • Systems and methods for knowledge discovery in spatial data

    Zoran Obradovic;Timothy E. Fiez;Slobodan Vucetic;Aleksandar Lazarevic

  • Continuous Conditional Random Fields for Regression in Remote Sensing

    Vladan Radosavljevic;Slobodan Vucetic;Zoran Obradovic

  • MS-kNN: Protein function prediction by integrating multiple data sources

    Liang Lan;Nemanja Djuric;Yuhong Guo;Slobodan Vucetic

  • Additional file 1 of An expanded evaluation of protein function prediction methods shows an improvement in accuracy

    Yuxiang Jiang;Tal Ronnen Oron;Wyatt T. Clark;Asma R. Bankapur

Frequent Co-Authors

Zoran Obradovic
Zoran Obradovic Temple University
Predrag Radivojac
Predrag Radivojac Northeastern University
A. Keith Dunker
A. Keith Dunker Indiana University
Christophe Dessimoz
Christophe Dessimoz University College London
Tapio Salakoski
Tapio Salakoski University of Turku
Daisuke Kihara
Daisuke Kihara Purdue University West Lafayette
David T. Jones
David T. Jones University College London
Celeste J. Brown
Celeste J. Brown University of Idaho
Steven E. Brenner
Steven E. Brenner University of California, Berkeley
Burkhard Rost
Burkhard Rost Technical University of Munich

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