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Molecular signature comprising 11 platelet-genes enables accurate blood-based diagnosis of NSCLC
Stable Feature Selection using Copula based Mutual Information
Challenges and possible solutions for decoding extranasal olfactory receptors
Analysis of single-cell transcriptomes links enrichment of olfactory receptors with cancer cell differentiation status and prognosis
The Cellular basis of loss of smell in 2019-nCoV-infected individuals
SelfE: Gene Selection via Self-Expression for Single-Cell Data
Integrative analysis and machine learning based characterization of single circulating tumor cells
Improved dropClust R package with integrative analysis support for scRNA-seq data
deepMc: Deep Matrix Completion for Imputation of Single-Cell RNA-seq Data
MenstruLoss: Sensor For Menstrual Blood Loss Monitoring
Staging System to Predict the Risk of Relapse in Multiple Myeloma Patients Undergoing Autologous Stem Cell Transplantation
McImpute : Matrix Completion Based Imputation for Single Cell RNA-seq Data
Texture Classification Using Deep Convolutional Neural Network with Ensemble Learning
Discovery of rare cells from voluminous single cell expression data
AutoImpute : Autoencoder based imputation of single-cell RNA-seq data
Structure aware Principal Component Analysis for single cell RNA-seq data
CellAtlasSearch: a scalable search engine for single cells
dropClust: Efficient clustering of ultra-large scRNA-seq data
Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors
ParSel: Parallel Selection of Micro‐RNAs for Survival Classification in Cancers
A scoring scheme for online feature selection: simulating model performance without retraining
FORKS: Finding Orderings Robustly using k-means and Steiner trees
Tumor-derived circulating endothelial cell clusters in colorectal cancer
Fast, scalable and accurate differential expression analysis for single cells
Pathway Informatics
FOCS: Fast Overlapped Community Search
Feature selection using feature dissimilarity measure and density-based clustering: Application to biological data
Weighted Markov Chain Based Aggregation of Biomolecule Orderings
Strong Nash Stability based Approach to Minimum Quasi Clique Partitioning
Determining a relative importance among ordered lists
XRDS Mobilizes
GRF: a greedy rank fusion algorithm for combining microRNA target orderings
Reformulated Kemeny Optimal Aggregation with Application in Consensus Ranking of microRNA Targets
Topological patterns in microRNA–gene regulatory network: studies in colorectal and breast cancer
Score based aggregation of microRNA target orderings
Participation of microRNAs in human interactome: extraction of microRNA–microRNA regulations
Entropy steered Kendall's tau measure for a fair Rank Aggregation
A novel measure for evaluating an ordered list: application in microRNA target prediction
paper
Molecular signature comprising 11 platelet-genes enables accurate blood-based diagnosis of NSCLC
Stable Feature Selection using Copula based Mutual Information
Challenges and possible solutions for decoding extranasal olfactory receptors
Analysis of single-cell transcriptomes links enrichment of olfactory receptors with cancer cell differentiation status and prognosis
The Cellular basis of loss of smell in 2019-nCoV-infected individuals
SelfE: Gene Selection via Self-Expression for Single-Cell Data
Integrative analysis and machine learning based characterization of single circulating tumor cells
Improved dropClust R package with integrative analysis support for scRNA-seq data
deepMc: Deep Matrix Completion for Imputation of Single-Cell RNA-seq Data
MenstruLoss: Sensor For Menstrual Blood Loss Monitoring
Staging System to Predict the Risk of Relapse in Multiple Myeloma Patients Undergoing Autologous Stem Cell Transplantation
McImpute : Matrix Completion Based Imputation for Single Cell RNA-seq Data
Texture Classification Using Deep Convolutional Neural Network with Ensemble Learning
Discovery of rare cells from voluminous single cell expression data
AutoImpute : Autoencoder based imputation of single-cell RNA-seq data
Structure aware Principal Component Analysis for single cell RNA-seq data
CellAtlasSearch: a scalable search engine for single cells
dropClust: Efficient clustering of ultra-large scRNA-seq data
Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors
ParSel: Parallel Selection of Micro‐RNAs for Survival Classification in Cancers
A scoring scheme for online feature selection: simulating model performance without retraining
FORKS: Finding Orderings Robustly using k-means and Steiner trees
Tumor-derived circulating endothelial cell clusters in colorectal cancer
Fast, scalable and accurate differential expression analysis for single cells
FOCS: Fast Overlapped Community Search
Feature selection using feature dissimilarity measure and density-based clustering: Application to biological data
Weighted Markov Chain Based Aggregation of Biomolecule Orderings
Strong Nash Stability based Approach to Minimum Quasi Clique Partitioning
Determining a relative importance among ordered lists
XRDS Mobilizes
GRF: a greedy rank fusion algorithm for combining microRNA target orderings
Reformulated Kemeny Optimal Aggregation with Application in Consensus Ranking of microRNA Targets
Topological patterns in microRNA–gene regulatory network: studies in colorectal and breast cancer
Score based aggregation of microRNA target orderings
Participation of microRNAs in human interactome: extraction of microRNA–microRNA regulations
Entropy steered Kendall's tau measure for a fair Rank Aggregation
A novel measure for evaluating an ordered list: application in microRNA target prediction
protocols
LSPCA: Structure preserving principal component analysis
FiRE: Fast rare cell discovery from single cell RNA-Seq
CellAtlasSearch: Single cell search engine
dropClust: Efficient clustering of Drop-seq data
ParSel: Feature selection for improved survival prediction
RCA: Noise free single cell clustering (Shyam Prabhakar’s lab)
OFS: Online feature selection
FOCS: Overlapping graph clustering
RA: Kemeny Optimal Rank Aggregation
protocol
LSPCA: Structure preserving principal component analysis
FiRE: Fast rare cell discovery from single cell RNA-Seq
CellAtlasSearch: Single cell search engine
dropClust: Efficient clustering of Drop-seq data
ParSel: Feature selection for improved survival prediction
RCA: Noise free single cell clustering (Shyam Prabhakar’s lab)
OFS: Online feature selection
FOCS: Overlapping graph clustering
RA: Kemeny Optimal Rank Aggregation
misc
About
The Sengupta Lab
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The Sengupta Lab
data
Disaggregation assay data visualization
Aggregation assay data visualization
chapter
Pathway Informatics
team
Arvind Iyer
Shivam Sharma
Ayushi Gupta
Shreya Mishra
Chitrita Goswami
Smriti Chawla
Sarita Poonia
Priya Rai
Krishan Gupta
Debarka Sengupta
news
indiabioscience.org: 'FiRE: Finding a needle in the haystack'
researchmatters.in: 'Finding the odd cell out'
jansatta.com: 'Unique algorithm of blood sample investigation'
The Hindu: 'Delhi researchers develop an algorithm to detect rare cells'
FiRE, discovering rare cells
Autoimpute, autoencoder based imputation technique
New Member in Lab
CellAtlasSearch
Sengupta Lab partners with Circle of Life Health Care Pvt. Ltd.
DropClust, speediest clustering algorithm
Brooking India Consortium
Sciencedaily
projects
Rapid rare cell discovery
Label-free, in silico detection of Circulating Tumor Cells (CTCs)
GPU accelerated single cell search
LSH for clustering ultra-large Drop-seq data
project
Rapid rare cell discovery
Label-free, in silico detection of Circulating Tumor Cells (CTCs)
GPU accelerated single cell search
LSH for clustering ultra-large Drop-seq data
Computational Biology
Indraprastha Institute of Information Technology
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