team
papers
- Utilizing Pretrained Vision Transfomers and Large Language Models for Epileptic Seizure Prediction
- Predicting peptide properties from mass spectrometry data using deep attention-based multitask network and uncertainty quantification
- PVTAD: Alzheimer’s Disease Diagnosis Using Pyramid Vision Transformer Applied to White Matter of T1-Weighted Structural MRI Data
- MLSPred-Bench: ML-Ready Benchmark Leveraging Seizure Detection EEG data for Predictive Models
- Making MS Omics Data ML-Ready: SpeCollate Protocols
- Heterogeneity Aware Distributed Machine Learning at the Wireless Edge for Health IoT Applications: An EEG Data Case Study
- Communication Evaluation of a Wireless 4-Channel Wearable EEG for Brain-Computer Interface (BCI) and Healthcare Applications
- Systems and methods for matching mass spectrometry data with a peptide database
- Statistical and Machine Learning Analysis of the Human Brain Functional Network in a Multi-Site Resting-State Functional MRI Database Framework
- Q-CASA Invited Speakers Quantum-Centric Supercomputing Strategies for Neuroscience problems: Challenges and Progress
- PPAD: a deep learning architecture to predict progression of Alzheimer’s disease
- High Performance Computing Algorithms for Accelerating Peptide Identification from Mass-Spectrometry Data Using Heterogeneous Supercomputers
- GPU-acceleration of the distributed-memory database peptide search of mass spectrometry data
- Energy Efficient AI/ML based Continuous Monitoring at the Edge: ECG and EEG Case Study
- Description of Dissolved Organic Matter Transformational Networks at the Molecular Level
- Confounding Effects on the Performance of Machine Learning Analysis of Static Functional Connectivity Computed from rs-fMRI Multi-site Data
- ASD-GResTM: Deep Learning Framework for ASD classification using Gramian Angular Field
- 22nd IEEE International Workshop on High Performance Computational Biology (HiCOMB 2023)
- Unsupervised structural classification of dissolved organic matter based on fragmentation pathways
- Systems and methods for peptide identification
- Systems and methods for measuring similarity between mass spectra and peptides
- Systems And Methods For Diagnosing Autism Spectrum Disorder Using fMRI Data
- SPERTL: Epileptic Seizure Prediction using EEG with ResNets and Transfer Learning
- Re-configurable Hardware for Computational Proteomics
- Need for High-Performance Computing for MS-Based Omics Data Analysis
- Molecular level characterization of DOM along a freshwater-to-estuarine coastal gradient in the Florida Everglades
- Machine-Learning and the Future of HPC for MS-Based Omics
- Introduction to Mass Spectrometry Data
- High-Performance Computing Strategy Using Distributed-Memory Supercomputers
- High-Performance Algorithms for Mass Spectrometry-Based Omics
- G-MSR: A GPU-Based Dimensionality Reduction Algorithm
- Fast Spectral Pre-processing for Big MS Data
- Existing HPC Methods and the Communication Lower Bounds for Distributed-Memory Computations for Mass Spectrometry-Based Omics Data
- Computational CPU-GPU Template for Pre-processing of Floating-Point MS Data
- Communication lower-bounds for distributed-memory computations for mass spectrometry based omics data
- Classification of Autism Spectrum Disorder Using rs-fMRI data and Graph Convolutional Networks
- Biomedical IoT: Enabling Technologies, Architectural Elements, Challenges, and Future Directions
- A Easy to Use Generalized Template to Support Development of GPU Algorithms
- TurboBFS: GPU Based Breadth-First Search (BFS) Algorithms in the Language of Linear Algebra
- TurboBC: A Memory Efficient and Scalable GPU Based Betweenness Centrality Algorithm in the Language of Linear Algebra
- SpeCollate: Deep cross-modal similarity network for mass spectrometry data based peptide deductions
- Source data: high performance computing framework for tera-scale database search of mass spectrometry data
- Simulation Testbed for Evaluating Distributed Querying and Searching of Mass Spectrometry Big Data in a Network-based Infrastructure
- Search feasibility in distributed MS-proteomics big data
- Real-time peptide identification from high-throughput mass-spectrometry data
- Neural Engineering Techniques for Autism Spectrum Disorder: Volume 1: Imaging and Signal Analysis
- Methods for Proteogenomics Data Analysis, Challenges, and Scalability Bottlenecks: A Survey
- Machine Learning methods for diagnosing Autism Spectrum Disorder and Attention-deficit/Hyperactivity Disorder using functional and structural MRI: A Survey
- High performance computing framework for tera-scale database search of mass spectrometry data
- HiCOPS: High Performance Computing Framework for Tera-Scale Database Search of Mass Spectrometry based Omics Data
- Graph Theoretic Approach for the Analysis of Comprehensive Mass-Spectrometry (MS/MS) Data of Dissolved Organic Matter
- Explainable and scalable machine learning algorithms for detection of autism spectrum disorder using fMRI data
- DeepCOVIDNet: Deep Convolutional Neural Network for COVID-19 Detection from Chest Radiographic Images
- Communication-avoiding micro-architecture to compute Xcorr scores for peptide identification
- Benchmarking mass spectrometry based proteomics algorithms using a simulated database
- ASD-SAENet: a sparse autoencoder, and deep-neural network model for detecting autism spectrum disorder (ASD) using fMRI data
- A Multi-Factorial Assessment of Functional Human Autistic Spectrum Brain Network Analysis
- ASD-DiagNet: A Hybrid Learning Approach for Detection of Autism Spectrum Disorder Using fMRI Data
- NGS-Integrator: An efficient tool for combining multiple NGS data tracks using minimum Bayes’ factors
- Methods and systems for compressing data
- High Performance and Machine Learning Algorithms for Brain fMRI Data
- Federated learning: A survey on enabling technologies, protocols, and applications
- Slm-transform: A method for memory-efficient indexing of spectra for database search in lc-ms/ms proteomics
- Optimized CNN-based diagnosis system to detect the pneumonia from chest radiographs
- NGS‐Integrator: A Tool for Combining Information from Multiple Genome‐Wide NGS Data Tracks Using Minimum Bayes Factors
- LBE: A Computational Load Balancing Algorithm for Speeding up Parallel Peptide Search in Mass-Spectrometry based Proteomics
- High-Performance Reductive Strategies for Big Data from LC-MS/MS Proteomics
- GPU-SFFT: A GPU based parallel algorithm for computing the Sparse Fast Fourier Transform (SFFT) of k-sparse signals
- GPU-DFC: A GPU-based parallel algorithm for computing dynamic-functional connectivity of big fMRI data
- Efficient shared peak counting in database peptide search using compact data structure for fragment-ion index
- Auto-ASD-Network: A technique based on Deep Learning and Support Vector Machines for diagnosing Autism Spectrum Disorder using fMRI data
- ASD-DiagNet: A hybrid learning approach for detection of Autism Spectrum Disorder using fMRI data
- 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
- Towards quantifying psychiatric diagnosis using machine learning algorithms and big fMRI data
- Similarity based classification of ADHD using Singular Value Decomposition
- Parallel sampling-pipeline for indefinite stream of heterogeneous graphs using OpenCL for FPGAs
- MaSS‐Simulator: A Highly Configurable Simulator for Generating MS/MS Datasets for Benchmarking of Proteomics Algorithms
- GPU-DAEMON: GPU algorithm design, data management & optimization template for array based big omics data
- Fast-GPU-PCC: A GPU-Based Technique to Compute Pairwise Pearson’s Correlation Coefficients for Time Series Data - An fMRI Study
- A Fourier-Based Data Minimization Algorithm for Fast and Secure Transfer of Big Genomic Datasets
- A deep learning-based data minimization algorithm for fast and secure transfer of big genomic datasets
- Scalable data structure to compress next-generation sequencing files and its application to compressive genomics
- Power-Efficient and Highly Scalable Parallel Graph Sampling using FPGAs
- GPU-PCC: A GPU Based Technique to Compute Pairwise Pearson's Correlation Coefficients for Big fMRI Data
- An out-of-core gpu based dimensionality reduction algorithm for big mass spectrometry data and its application in bottom-up proteomics
- A new cryptography algorithm to protect cloud-based healthcare services
- A Hybrid MPI-OpenMP Strategy to Speedup the Compression of Big Next-Generation Sequencing Datasets
- Systems-level analysis reveals selective regulation of Aqp2 gene expression by vasopressin
- Selected Papers from BICoB2015
- Reductive Analytics on Big MS Data leads to tremendous reduction in time for peptide deduction
- MS-REDUCE: an ultrafast technique for reduction of big mass spectrometry data for high-throughput processing
- Introduction to the selected papers from the 7th International Conference on Bioinformatics and Computational Biology (BICoB 2015)
- GPU-ArraySort: A parallel, in-place algorithm for sorting large number of arrays
- Data Aware Communication for Energy Harvesting Sensor Networks
- A variable-length network encoding protocol for big genomic data
- A Parallel Peptide Indexer and Decoy Generator for Crux Tide using OpenMP
- On the sampling of big mass spectrometry data
- Design and implementation of network transfer protocol for big genomic data
- Big data proteogenomics and high performance computing: Challenges and opportunities
- Autophagic degradation of aquaporin-2 is an early event in hypokalemia-induced nephrogenic diabetes insipidus
- A parallel algorithm for compression of big next-generation sequencing datasets
- A High Performance Architecture for an Exact Match Short-Read Aligner Using Burrows-Wheeler Aligner on FPGAs
- Global analysis of the effects of the V2 receptor antagonist satavaptan on protein phosphorylation in collecting duct
- Foreword to the special issue on selected papers from the 6th International Conference on Bioinformatics and Computational Biology (BICoB 2014).
- Exploiting thread-level and instruction-level parallelism to cluster mass spectrometry data using multicore architectures
- Cams-rs: clustering algorithm for large-scale mass spectrometry data using restricted search space and intelligent random sampling
- A knowledge base of vasopressin actions in the kidney
- 6th International Conference on Bioinformatics and Computational Biology (BICoB 2014)
- Quantitative phosphoproteomics implicates clusters of proteins involved in cell‐cell adhesion and transcriptional regulation in the vasopressin signaling network
- Proteome-wide measurement of protein half-lives and translation rates in vasopressin-sensitive collecting duct cells
- PhosSA: Fast and accurate phosphorylation site assignment algorithm for mass spectrometry data
- Foreword to the special issue on selected papers from the 5th International Conference on Bioinformatics and Computational Biology (BICoB 2013)
- A high performance algorithm for clustering of large-scale protein mass spectrometry data using multi-core architectures
- A Graphical User Interface (GUI) for Phosphorylation Site Assignment of Protein Mass Spectrometry Data
- Quantitative phosphoproteomics in nuclei of vasopressin-sensitive renal collecting duct cells
- Proteomic and Metabolomic Approaches to Cell Physiology and Pathophysiology: Quantitative phosphoproteomics in nuclei of vasopressin-sensitive renal collecting duct cells
- NHLBI-AbDesigner: an online tool for design of peptide-directed antibodies
- Identifying protein kinase target preferences using mass spectrometry
- High performance phosphorylation site assignment algorithm for mass spectrometry data using multicore systems
- Dynamics of the G protein-coupled vasopressin V2 receptor signaling network revealed by quantitative phosphoproteomics
- CP hos: a program to calculate and visualize evolutionarily conserved functional phosphorylation sites
- An efficient dynamic programming algorithm for phosphorylation site assignment of large-scale mass spectrometry data
- An efficient algorithm for clustering of large-scale mass spectrometry data
- A high performance multiple sequence alignment system for pyrosequencing reads from multiple reference genomes
- Mining temporal patterns from iTRAQ mass spectrometry (LC-MS/MS) data
- Mapping‐based temporal pattern mining algorithm (MTPMA) identifies unique clusters of phosphopeptides regulated by vasopressin in collecting duct
- Large‐scale iTRAQ‐based quantification of phosphorylation changes during vasopressin signaling
- Parallel Algorithm for Center Star Sequence and Alignments with Applications to Short Reads
- High performance computational biology algorithms
- A graph-theoretic framework for efficient computation of HMM based motif finder
- Pyro-align: Sample-align based multiple alignment system for pyrosequencing reads of large number
- Multiple sequence alignment system for pyrosequencing reads
- An Overview of Multiple Sequence Alignment Systems
- A domain decomposition strategy for alignment of multiple biological sequences on multiprocessor platforms
- Sample-align-d: A high performance multiple sequence alignment system using phylogenetic sampling and domain decomposition
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