S. Tripathi

发表

A data-centric review of deep transfer learning with applications to text data

M. Dehmer, F. Emmert-Streib, Samar Bashath, 2021, Inf. Sci..

Ensuring the statistical soundness of competitive gene set approaches: gene filtering and genome-scale coverage are essential

G. Glazko, F. Emmert-Streib, S. Tripathi, 2013, Nucleic acids research.

The human disease network

M. Dehmer, F. Emmert-Streib, S. Tripathi, 2013 .

Harnessing the complexity of gene expression data from cancer: from single gene to structural pathway methods

F. Emmert-Streib, S. Tripathi, Ricardo de Matos Simoes, 2012, Biology Direct.

Prognostic gene expression signatures of breast cancer are lacking a sensible biological meaning

G. Glazko, M. Dehmer, O. Yli-Harja, 2021, Scientific reports.

A Bayesian analysis of the chromosome architecture of human disorders by integrating reductionist data

G. Glazko, M. Dehmer, F. Emmert-Streib, 2012, Scientific Reports.

Comprehensive molecular pathology analysis of small bowel adenocarcinoma reveals novel targets with potential for clinical utility

M. Salto‐Tellez, P. Maxwell, P. Hamilton, 2015, Oncotarget.

Overview of Public Cancer Databases, Resources, and Visualization Tools

M. Dehmer, F. Emmert-Streib, S. Tripathi, 2013 .

Discrimination Power of Polynomial-Based Descriptors for Graphs by Using Functional Matrices

M. Dehmer, Yongtang Shi, S. Tripathi, 2015, PloS one.

Computational Analysis of the structural properties of Economic and Financial Networks

Matthias Dehmer, Olli Yli-Harja, Herbert Jodlbauer, 2017, 1710.04455.

The usefulness of topological indices

M. Dehmer, F. Emmert-Streib, S. Tripathi, 2022, Inf. Sci..

An Introductory Review of Deep Learning for Prediction Models With Big Data

M. Dehmer, F. Emmert-Streib, S. Tripathi, 2020, Frontiers in Artificial Intelligence.

Organizational structure and the periphery of the gene regulatory network in B-cell lymphoma

Frank Emmert-Streib, Ricardo de Matos Simoes, Shailesh Tripathi, 2012, BMC Systems Biology.

Comparison of module detection algorithms in protein networks and investigation of the biological meaning of predicted modules

Matthias Dehmer, Frank Emmert-Streib, Salissou Moutari, 2016, BMC Bioinformatics.

L1000 Viewer: A Search Engine and Web Interface for the LINCS Data Repository

Matthias Dehmer, Frank Emmert-Streib, Shailesh Tripathi, 2019, Front. Genet..

Systems Pharmacogenomic Landscape of Drug Similarities from LINCS data: Drug Association Networks

Olli Yli-Harja, Shailesh Tripathi, Matthias Dehmer, 2019, Scientific Reports.

Harnessing the biological complexity of Big Data from LINCS gene expression signatures

Meenakshisundaram Kandhavelu, Shailesh Tripathi, Matthias Dehmer, 2018, PloS one.

Visualization of Biological Networks Using NetBioV: Applications in Biology, Medicine, and Chemistry

Matthias Dehmer, Frank Emmert-Streib, Salissou Moutari, 2016 .

Gene expression in the cell cycle of human T lymphocytes: I. Predicted gene and protein networks

C. Nicolini, C. Nicolini, S. Tripathi, 2006, Journal of cellular biochemistry.

On the degeneracy of the Randić entropy and related graph measures

Yongtang Shi, Zengqiang Chen, Matthias Dehmer, 2019, Inf. Sci..

Towards detecting structural branching and cyclicity in graphs: A polynomial-based approach

Yongtang Shi, Zengqiang Chen, Matthias Dehmer, 2019, Inf. Sci..

Graph measures with high discrimination power revisited: A random polynomial approach

Yongtang Shi, Zengqiang Chen, Matthias Dehmer, 2018, Inf. Sci..

Highly unique network descriptors based on the roots of the permanental polynomial

Bo Hu, Yongtang Shi, Matthias Dehmer, 2017, Inf. Sci..

NetBioV: an R package for visualizing large network data in biology and medicine

Matthias Dehmer, Frank Emmert-Streib, Shailesh Tripathi, 2014, Bioinform..

Graph-based exploitation of gene ontology using GOxploreR for scrutinizing biological significance

Frank Emmert-Streib, Olli Yli-Harja, Shailesh Tripathi, 2020, Scientific Reports.

Assessment Method for a Power Analysis to Identify Differentially Expressed Pathways

Frank Emmert-Streib, Shailesh Tripathi, F. Emmert-Streib, 2012, PloS one.

The Contribution of Data-Driven Technologies in Achieving the Sustainable Development Goals

S. Tripathi, H. Jodlbauer, Manuel Brunner, 2022, Sustainability.

Understanding the World Economy in Terms of Networks: A Survey of Data-Based Network Science Approaches on Economic Networks

Matthias Dehmer, Olli Yli-Harja, Shailesh Tripathi, 2018, Front. Appl. Math. Stat..

Divide and conquer anomaly detection: A case study predicting defective engines

Herbert Jodlbauer, Shailesh Tripathi, David Muhr, 2020 .

Ensuring the Robustness and Reliability of Data-Driven Knowledge Discovery Models in Production and Manufacturing

Matthias Dehmer, Frank Emmert-Streib, Herbert Jodlbauer, 2020, Frontiers in Artificial Intelligence.

Large scale predictability analysis of process variables from injection molding machines

S. Tripathi, H. Jodlbauer, C. Mittermayr, 2020, ISM.

An adaptive machine learning methodology to determine manufacturing process parameters for each part

S. Tripathi, H. Jodlbauer, David Muhr, 2020, ISM.

Constrained Covariance Matrices With a Biologically Realistic Structure: Comparison of Methods for Generating High-Dimensional Gaussian Graphical Models

Matthias Dehmer, Frank Emmert-Streib, Shailesh Tripathi, 2019, Front. Appl. Math. Stat..

sgnesR: An R package for simulating gene expression data from an underlying real gene network structure considering delay parameters

M. Dehmer, O. Yli-Harja, F. Emmert-Streib, 2017, BMC Bioinformatics.

Identifying key interactions between process variables of different material categories using mutual information-based network inference method

F. Emmert-Streib, S. Tripathi, H. Jodlbauer, 2021, ISM.

Comprehensive molecular pathology analysis of small bowel adenocarcinoma reveals novel targets with potential for clinical utility

M. Salto‐Tellez, P. Maxwell, P. Hamilton, 2015 .

A Survey on Cross‐Virtuality Analytics

C. Holzmann, S. Tripathi, H. Jodlbauer, 2022, Comput. Graph. Forum.

samExploreR: exploring reproducibility and robustness of RNA-seq results based on SAM files

Matthias Dehmer, Frank Emmert-Streib, Galina V. Glazko, 2016, Bioinform..

NetBioV: an R package for visualizing large network data in biology and medicine

M. Dehmer, F. Emmert-Streib, S. Tripathi, 2014, Bioinform..

Measuring the complexity of directed graphs: A polynomial-based approach

Jin Tao, Zengqiang Chen, Abbe Mowshowitz, 2019, PloS one.

Linear vs. Symbolic Regression for Adaptive Parameter Setting in Manufacturing Processes

Jan Zenisek, Herbert Jodlbauer, Shailesh Tripathi, 2018, DATA.

Analyzing the Scholarly Literature of Digital Twin Research: Trends, Topics and Structure

M. Dehmer, F. Emmert-Streib, S. Tripathi, 2023, IEEE Access.

Approaches to Identify Relevant Process Variables in Injection Moulding using Beta Regression and SVM

Matthias Dehmer, Herbert Jodlbauer, Shailesh Tripathi, 2019, DATA.

A Network based Approach for Reducing Variant Diversity in Production Planning and Control

Herbert Jodlbauer, Shailesh Tripathi, Sonja Strasser, 2021, DATA.

On efficient network similarity measures

Yongtang Shi, Matthias Dehmer, Abbe Mowshowitz, 2019, Appl. Math. Comput..