A Computational Analysis of Protein Sequences for Cyclophilin Superfamily using Feature Extraction. - Neha Mehra; Aruna Tiwari; Milind B. Ratnaparkhe; Neha Bharill (SSCI, 2018)

Vector Quantized Spectral Clustering applied to Soybean Whole Genome Sequences. - Aditya A. Shastri; Kapil Ahuja; Milind B. Ratnaparkhe; Aditya Shah; Aishwary Gagrani; Anant Lal (CoRR, 2018)

Probabilistically Sampled and Spectrally Clustered Plant Genotypes using Phenotypic Characteristics. - Aditya A. Shastri; Kapil Ahuja; Milind B. Ratnaparkhe; Yann Busnel (CoRR, 2020)

Scalable Fuzzy Clustering-based Regression to Predict the Isoelectric Points of the Plant Protein Sequences using Apache Spark. - Ajay Choudhary; Preeti Jha; Aruna Tiwari; Neha Bharill; Milind B. Ratnaparkhe (FUZZ-IEEE, 2021)

Apache Spark based kernelized fuzzy clustering framework for single nucleotide polymorphism sequence analysis. - Preeti Jha; Aruna Tiwari; Neha Bharill; Milind B. Ratnaparkhe; Mukkamalla Mounika; Neha Nagendra (Comput. Biol. Chem., 2021)

Scalable incremental fuzzy consensus clustering algorithm for handling big data. - Preeti Jha; Aruna Tiwari; Neha Bharill; Milind B. Ratnaparkhe; Neha Nagendra; Mukkamalla Mounika (Soft Comput., 2021)

A Novel Scalable Kernelized Fuzzy Clustering Algorithms Based on In-Memory Computation for Handling Big Data. - Preeti Jha; Aruna Tiwari; Neha Bharill; Milind B. Ratnaparkhe; Mukkamalla Mounika; Neha Nagendra (IEEE Trans. Emerg. Top. Comput. Intell., 2021)

A Novel Scalable Feature Extraction Approach for COVID-19 Protein Sequences and their Cluster Analysis with Kernelized Fuzzy Algorithm. - Preeti Jha; Aruna Tiwari; Neha Bharill; Milind B. Ratnaparkhe; Om Prakash Patel; Nilagiri Harshith; Soundarya Lahari Solasa (BigComp, 2022)

HPC enabled a Novel Deep Fuzzy Scalable Clustering Algorithm and its Application for Protein Data. - Preeti Jha; Aruna Tiwari; Neha Bharill; Milind B. Ratnaparkhe; Om Prakash Patel; Vaibhav Anand; Sudhanshu Arya; Tanmay Singh (CIBCB, 2022)

A Hybrid Feature Selection Approach for Data Clustering Based on Ant Colony Optimization. - Rajesh Dwivedi; Aruna Tiwari; Neha Bharill; Milind B. Ratnaparkhe (ICONIP (3), 2022)

HPC Based Scalable Logarithmic Kernelized Fuzzy Clustering Algorithms for Handling Big Data. - Preeti Jha; Aruna Tiwari; Neha Bharill; Milind B. Ratnaparkhe; Om Prakash Patel; Sawarkar Saloni; Namani Sreeharsh (ICONIP (5), 2022)

High-Performance Computing based Scalable Online Fuzzy Clustering Algorithms for Big Data. - Preeti Jha; Aruna Tiwari; Neha Bharill; Milind B. Ratnaparkhe; Om Prakash Patel; Rapolu Pulakitha; Aditi Chauhan (SSCI, 2022)

A Novel Scalable Apache Spark Based Feature Extraction Approaches for Huge Protein Sequence and their Clustering Performance Analysis. - Preeti Jha; Aruna Tiwari; Neha Bharill; Milind B. Ratnaparkhe; Om Prakash Patel; Nilagiri Harshith; Mukkamalla Mounika; Neha Nagendra (CoRR, 2022)

A Novel Feature Extraction Approach for the Clustering and Classification of Genome Sequences. - Rajesh Dwivedi; Aruna Tiwari; Neha Bharill; Milind B. Ratnaparkhe; Abhishek Tripathi; Preeti Jha (SSCI, 2023)

Scalable Kernelized Deep Fuzzy Clustering Algorithms for Big Data. - Preeti Jha; Aruna Tiwari; Neha Bharill; Milind B. Ratnaparkhe; Om Prakash Patel; Anjali Gupta; Deepali Sukhija; Deepika Sukhija; Rajesh Dwivedi (SSCI, 2023)

A Novel Sampled Clustering Algorithm for Rice Phenotypic Data. - Mithun Singh; Kapil Ahuja; Milind B. Ratnaparkhe (CoRR, 2023)

Apache Spark-based scalable feature extraction approaches for protein sequence and their clustering performance analysis. - Preeti Jha; Aruna Tiwari; Neha Bharill; Milind B. Ratnaparkhe; Om Prakash Patel; Nilagiri Harshith; Mukkamalla Mounika; Neha Nagendra (Int. J. Data Sci. Anal., 2023)

A novel apache spark-based 14-dimensional scalable feature extraction approach for the clustering of genomics data. - Rajesh Dwivedi; Aruna Tiwari; Neha Bharill; Milind B. Ratnaparkhe; Parul Mogre; Pranjal Gadge; Kethavath Jagadeesh (J. Supercomput., 2024)

An incremental clustering method based on multiple objectives for dynamic data analysis. - Rajesh Dwivedi; Aruna Tiwari; Neha Bharill; Milind B. Ratnaparkhe; Rishabh Soni; Rahul Mahbubani; Saket Kumar (Multim. Tools Appl., 2024)

A taxonomy of unsupervised feature selection methods including their pros, cons, and challenges. - Rajesh Dwivedi; Aruna Tiwari; Neha Bharill; Milind B. Ratnaparkhe; Alok Kumar Tiwari (J. Supercomput., 2024)

On construction of data preprocessing for real-life SoyLeaf dataset & disease identification using Deep Learning Models. - Sujata Gudge; Aruna Tiwari; Milind B. Ratnaparkhe; Preeti Jha (Comput. Biol. Chem., 2025)

A novel chemical property-based, alignment-free scalable feature extraction method for genomic data clustering. - Rajesh Dwivedi; Aruna Tiwari; Neha Bharill; Milind B. Ratnaparkhe; Saurabh Kumar Singh; Abhishek Tripathi (Comput. Electr. Eng., 2025)

A scalable method for extracting features using a complex network from SNP sequences and clustering using the scalable Max of Min algorithm. - Achint Kumar Kansal; Aruna Tiwari; Milind B. Ratnaparkhe; Rajesh Dwivedi; Preeti Jha (Soft Comput., 2025)