Kanchana Padmanabhan

Works (9)

Updated: July 6th, 2023 11:35

2015 article

On the data-driven inference of modulatory networks in climate science: an application to West African rainfall

González, D. L., II, Angus, M. P., Tetteh, I. K., Bello, G. A., Padmanabhan, K., Pendse, S. V., … Samatova, N. F. (2015, January 13). Nonlinear Processes in Geophysics.

By: D. González n, M. Angus n, I. Tetteh n, G. Bello n, K. Padmanabhan n, S. Pendse n, S. Srinivas n, J. Yu ...

topics (OpenAlex): Climate variability and models; Hydrology and Drought Analysis; Hydrological Forecasting Using AI
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UN Sustainable Development Goal Categories
13. Climate Action (Web of Science; OpenAlex)
Source: Web Of Science
Added: August 6, 2018

2013 article

Coupled Heterogeneous Association Rule Mining (CHARM): Application Toward Inference of Modulatory Climate Relationships

Gonzalez, D. L., II, Pendse, S. V., Padmanabhan, K., Angus, M. P., Tetteh, I. K., Srinivas, S., … Samatova, N. F. (2013, December 1).

By: D. Gonzalez n, S. Pendse n, K. Padmanabhan n, M. Angus n, I. Tetteh n, S. Srinivas n, A. Villanes n, F. Semazzi n, V. Kumar *, N. Samatova n

author keywords: association rules; climate; data coupling; discovery
topics (OpenAlex): Data Management and Algorithms; Data Mining Algorithms and Applications; Hydrological Forecasting Using AI
TL;DR: Coupled Heterogeneous Association Rule Mining (CHARM), a computationally efficient methodology that mines higher-order relationships between these subsystems' anomalous temporal phases with respect to their effect on the system's response, is presented. (via Semantic Scholar)
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UN Sustainable Development Goal Categories
13. Climate Action (Web of Science; OpenAlex)
Source: Web Of Science
Added: August 6, 2018

2012 article

Functional Annotation of Hierarchical Modularity

Padmanabhan, K., Wang, K., & Samatova, N. F. (2012, April 4). PLoS ONE.

By: K. Padmanabhan n, K. Wang  n & N. Samatova n

MeSH headings : Algorithms; Cluster Analysis; Computational Biology / methods; Databases, Factual; Metabolic Networks and Pathways; Protein Interaction Mapping; Saccharomyces cerevisiae / genetics; Saccharomyces cerevisiae / metabolism; Saccharomyces cerevisiae Proteins / genetics; Saccharomyces cerevisiae Proteins / metabolism
topics (OpenAlex): Bioinformatics and Genomic Networks; Microbial Metabolic Engineering and Bioproduction; Computational Drug Discovery Methods
TL;DR: The complementary method provides the hierarchical functional annotation of the modules and their hierarchically organized components by directly incorporating the functional taxonomy information into the hierarchy search process and by allowing multi-functional genes to be part of more than one component in the hierarchy. (via Semantic Scholar)
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Source: Web Of Science
Added: August 6, 2018

2012 article

In-silico identification of phenotype-biased functional modules

Padmanabhan, K., Wilson, K., Rocha, A. M., Wang, K., Mihelcic, J. R., & Samatova, N. F. (2012, June 21). Proteome Science.

By: K. Padmanabhan n, K. Wilson*, A. Rocha *, K. Wang  n, J. Mihelcic * & N. Samatova n

topics (OpenAlex): Microbial Metabolic Engineering and Bioproduction; Bioinformatics and Genomic Networks; Biofuel production and bioconversion
TL;DR: A methodology to identify phenotype-biased cellular subsystems that are more prone to occur in phenotype-expressing organisms than in phenotype non-expressing organisms is proposed and shown the effectiveness of the methodology by applying it to several target phenotypes. (via Semantic Scholar)
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Source: Web Of Science
Added: August 6, 2018

2012 article

NIBBS-Search for Fast and Accurate Prediction of Phenotype-Biased Metabolic Systems

Schmidt, M. C., Rocha, A. M., Padmanabhan, K., Shpanskaya, Y., Banfield, J., Scott, K., … Samatova, N. F. (2012, May 10). PLoS Computational Biology, Vol. 8.

By: M. Schmidt n , A. Rocha *, K. Padmanabhan n, Y. Shpanskaya *, J. Banfield *, K. Scott *, J. Mihelcic *, N. Samatova n

MeSH headings : Algorithms; Animals; Computer Simulation; Data Mining / methods; Databases, Protein; Humans; Metabolome / physiology; Models, Biological; Periodicals as Topic; Phenotype; Protein Interaction Mapping / methods; Proteome / metabolism; Signal Transduction / physiology
topics (OpenAlex): Microbial Metabolic Engineering and Bioproduction; Biofuel production and bioconversion; Bioinformatics and Genomic Networks
TL;DR: Network Instance-Based Biased Subgraph Search (NIBBS) is a graph-theoretic method for genome-scale metabolic network comparative analysis that can identify metabolic systems that are statistically biased toward phenotype-expressing organismal networks. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries
Added: August 6, 2018

2011 article

DENSE: efficient and prior knowledge-driven discovery of phenotype-associated protein functional modules

Hendrix, W., Rocha, A. M., Padmanabhan, K., Choudhary, A., Scott, K., Mihelcic, J. R., & Samatova, N. F. (2011, October 24). BMC Systems Biology.

By: W. Hendrix n, A. Rocha *, K. Padmanabhan n, A. Choudhary*, K. Scott *, J. Mihelcic *, N. Samatova n

MeSH headings : Animals; Binding Sites; Cattle; Cell Movement; Cells, Cultured; Computer Simulation; Extracellular Matrix / metabolism; Fibronectins / metabolism; Humans; Models, Biological; Neuropilin-1 / metabolism; Pancreatic Elastase / metabolism; Phenotype; Rats; Receptors, Vascular Endothelial Growth Factor / metabolism; Signal Transduction; Systems Biology; Vascular Endothelial Growth Factor A / chemistry; Vascular Endothelial Growth Factor A / metabolism; Vascular Endothelial Growth Factor A / physiology
topics (OpenAlex): Microbial Metabolic Engineering and Bioproduction; Bioinformatics and Genomic Networks; Computational Drug Discovery Methods
TL;DR: A fast and theoretically guranteed method called DENSE (Dense and ENriched Subgraph Enumeration) that can take in as input a biologist's prior knowledge as a set of query proteins and identify all the dense functional modules in a biological network that contain some part of the query vertices is introduced. (via Semantic Scholar)
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Source: Web Of Science
Added: August 6, 2018

2011 article

Efficient α, β-motif finder for identification of phenotype-related functional modules

Schmidt, M. C., Rocha, A. M., Padmanabhan, K., Chen, Z., Scott, K., Mihelcic, J. R., & Samatova, N. F. (2011, November 11). BMC Bioinformatics, Vol. 12.

By: M. Schmidt n , A. Rocha *, K. Padmanabhan n, Z. Chen n, K. Scott *, J. Mihelcic *, N. Samatova n

MeSH headings : Acids / metabolism; Algorithms; Bacteria / genetics; Bacteria / metabolism; Citric Acid Cycle; Computing Methodologies; Hydrogen / metabolism; Phenotype; Proteobacteria
topics (OpenAlex): Machine Learning in Bioinformatics; Ubiquitin and proteasome pathways; Bioinformatics and Genomic Networks
TL;DR: A methodology that can identify potential statistically significant phenotype-related functional modules that are in at least α networks of phenotype-expressing organisms but appear in no more than β networks of organisms that do not exhibit the target phenotype is proposed. (via Semantic Scholar)
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UN Sustainable Development Goal Categories
6. Clean Water and Sanitation (OpenAlex)
Sources: Web Of Science, NC State University Libraries
Added: August 6, 2018

journal article

Characterizing gene and protein crosstalks in subjects at risk of developing Alzheimer's disease: A new computational approach

Padmanabhan, K., Nudelman, K., Harenberg, S., Bello, G., Sohn, D., Shpanskaya, K., … Samatova, N. F. Processes, 5(3).

By: K. Padmanabhan, K. Nudelman, S. Harenberg, G. Bello, D. Sohn, K. Shpanskaya, P. Dikshit, P. Yerramsetty ...

Source: NC State University Libraries
Added: August 6, 2018

report

Community detection in large-scale networks: A Survey and empirical evaluation

Harenberg, S., Bello, G. A., Gjeltema, L., Ranshous, S., Harlalka, J., Seay, R., … Samatova, N. In Technical Report- Not held in TRLN member libraries (p. 2014).

By: S. Harenberg, G. Bello, L. Gjeltema, S. Ranshous, J. Harlalka, R. Seay, K. Padmanabhan, N. Samatova

Source: NC State University Libraries
Added: August 6, 2018

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