| Nome |
# |
|
Automated Segmentation of Cells with IHC Membrane Staining, file e384c42e-114c-d4b2-e053-9f05fe0a1d67
|
6.748
|
|
Computer-aided techniques for Chromogenic Immunohistochemistry: Status and Directions, file e384c42e-251c-d4b2-e053-9f05fe0a1d67
|
1.051
|
|
Automated segmentation of tissue images for computerized IHC analysis, file e384c42e-02f7-d4b2-e053-9f05fe0a1d67
|
892
|
|
Automated DNA Fragments Recognition and Sizing through AFM Image Processing, file e384c42d-f65f-d4b2-e053-9f05fe0a1d67
|
784
|
|
Achieving the Way for Automated Segmentation of Nuclei in Cancer Tissue Images through Morphology-Based Approach: a Quantitative Evaluation, file e384c42e-0935-d4b2-e053-9f05fe0a1d67
|
680
|
|
Acceleration of Coarse Grain Molecular Dynamics on GPU Architectures, file e384c42e-1ebe-d4b2-e053-9f05fe0a1d67
|
669
|
|
An automated approach to the segmentation of HEp-2 cells for the indirect immunofluorescence ANA test, file e384c42e-360e-d4b2-e053-9f05fe0a1d67
|
655
|
|
Reverse Engineering of TopHat: Splice Junction Mapper for Improving Computational Aspect, file e384c42e-1caa-d4b2-e053-9f05fe0a1d67
|
636
|
|
Subclass Discriminant Analysis of Morphological and Textural Features for HEp-2 Staining Pattern Classification, file e384c42e-2a29-d4b2-e053-9f05fe0a1d67
|
623
|
|
A novel pipeline for V(D)J junction identification using RNA-Seq paired-end reads, file e384c42e-2122-d4b2-e053-9f05fe0a1d67
|
609
|
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Applying Textural Features to the Classification of HEp-2 Cell Patterns in IIF images, file e384c42e-2433-d4b2-e053-9f05fe0a1d67
|
564
|
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A Novel Gaussian Extrapolation Approach for 2D Gel Electrophoresis Saturated Protein Spots, file e384c42e-1f99-d4b2-e053-9f05fe0a1d67
|
550
|
|
Automatic Intrinsic DNA Curvature Computation from AFM Images, file e384c42d-f660-d4b2-e053-9f05fe0a1d67
|
548
|
|
Classification of HEp-2 staining patterns in ImmunoFluorescence images. Comparison of Support Vector Machines and Subclass Discriminant Analysis strategies, file e384c42e-201b-d4b2-e053-9f05fe0a1d67
|
536
|
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miREE: miRNA Recognition Elements Ensemble, file e384c42e-14a0-d4b2-e053-9f05fe0a1d67
|
508
|
|
A novel Gaussian fitting approach for 2D gel electrophoresis saturated protein spots, file e384c42e-1bf2-d4b2-e053-9f05fe0a1d67
|
503
|
|
One Decade of Development and Evolution of MicroRNA Target Prediction Algorithms, file e384c42e-1ebb-d4b2-e053-9f05fe0a1d67
|
499
|
|
Automated Discrimination of Pathological Regions in Tissue Images: Unsupervised Clustering vs Supervised SVM Classification, file e384c42d-fdd2-d4b2-e053-9f05fe0a1d67
|
452
|
|
ANAlyte: a modular image analysis tool for ANA testing with Indirect Immunofluorescence, file e384c42e-b0eb-d4b2-e053-9f05fe0a1d67
|
426
|
|
Computational Methods for CLIP-seq Data Processing, file e384c42e-35d0-d4b2-e053-9f05fe0a1d67
|
402
|
|
A novel framework for chimeric transcript detection based on accurate gene fusion model, file e384c42e-0f25-d4b2-e053-9f05fe0a1d67
|
373
|
|
Motion artifact correction in ASL images: an improved automated procedure, file e384c42e-0e3b-d4b2-e053-9f05fe0a1d67
|
344
|
|
miR-SEA: miRNA Seed Extension based Aligner Pipeline for NGS Expression Level Extraction, file e384c42e-32c5-d4b2-e053-9f05fe0a1d67
|
319
|
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MicroRNA/mRNA interactions underlying colorectal cancer molecular subtypes, file e384c42e-7820-d4b2-e053-9f05fe0a1d67
|
319
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Joint co-clustering: co-clustering of genomic and clinical bioimaging data, file e384c42d-f661-d4b2-e053-9f05fe0a1d67
|
305
|
|
Pegasus: a comprehensive annotation and prediction tool for detection of driver gene fusions in cancer, file e384c42e-3285-d4b2-e053-9f05fe0a1d67
|
282
|
|
New Software for the Identification and Characterization
of Peptides Generated during Fontina Cheese Ripening
Using Mass Spectrometry Data, file e384c42e-1b6f-d4b2-e053-9f05fe0a1d67
|
266
|
|
Optimizing Splicing Junction Detection in Next Generation Sequencing Data on a Virtual-GRID Infrastructure, file e384c42e-1fb4-d4b2-e053-9f05fe0a1d67
|
241
|
|
Dynamic Gap Selector: A Smith Waterman Sequence Alignment Algorithm with Affine Gap Model Optimisation, file e384c42e-3007-d4b2-e053-9f05fe0a1d67
|
239
|
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Selective analysis of cancer-cell intrinsic transcriptional traits defines novel clinically relevant subtypes of colorectal cancer, file e384c42f-7f88-d4b2-e053-9f05fe0a1d67
|
136
|
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Unsupervised HEp-2 mitosis recognition in Indirect Immunofluorescence Imaging, file e384c431-a611-d4b2-e053-9f05fe0a1d67
|
107
|
|
Indentifying sub-network functional modules in protein undirected networks, file e384c42f-23ef-d4b2-e053-9f05fe0a1d67
|
102
|
|
VDJSeq-Solver: In Silico V(D)J Recombination Detection tool, file e384c431-9d7b-d4b2-e053-9f05fe0a1d67
|
99
|
|
Multi-omics classification on kidney samples exploiting uncertainty-aware models, file e384c432-6221-d4b2-e053-9f05fe0a1d67
|
94
|
|
Colorectal Cancer Classification using Deep Convolutional Networks. An Experimental Study, file e384c431-75d3-d4b2-e053-9f05fe0a1d67
|
91
|
|
Unsupervised Multi-Omic Data Fusion: the Neural Graph Learning Network, file e384c432-e5be-d4b2-e053-9f05fe0a1d67
|
80
|
|
DEEPrior: a deep learning tool for the prioritization of gene fusions, file e384c431-7422-d4b2-e053-9f05fe0a1d67
|
76
|
|
Optimizing Quality Inspection and Control in Powder Bed Metal Additive Manufacturing: Challenges and Research Directions, file e384c432-e262-d4b2-e053-9f05fe0a1d67
|
75
|
|
Automated 3D immunofluorescence analysis of Dorsal Root Ganglia for the investigation of neural circuit alterations: a preliminary study., file e384c431-72b0-d4b2-e053-9f05fe0a1d67
|
66
|
|
FuGePrior: A novel gene fusion prioritization algorithm based on accurate fusion structure analysis in cancer RNA-seq samples, file e384c431-c6e7-d4b2-e053-9f05fe0a1d67
|
66
|
|
Mining textural knowledge in biological images: applications, methods and trends, file e384c431-af5e-d4b2-e053-9f05fe0a1d67
|
65
|
|
On the relevance of a complete characterisation of miRNAs, isomiRs and miRNA-mRNA interaction sites through miRNA-specific alignment tools, file e384c42d-d848-d4b2-e053-9f05fe0a1d67
|
60
|
|
A Bayesian approach to Expert Gate Incremental Learning, file e384c433-6488-d4b2-e053-9f05fe0a1d67
|
59
|
|
Single-cell DNA Sequencing Data: a Pipeline for Multi-Sample Analysis, file e384c431-0884-d4b2-e053-9f05fe0a1d67
|
54
|
|
A Deep Learning Approach to the Screening of Oncogenic Gene Fusions in Humans, file e384c431-995e-d4b2-e053-9f05fe0a1d67
|
53
|
|
Effective evaluation of clustering algorithms on single-cell CNA data, file e384c432-6cd8-d4b2-e053-9f05fe0a1d67
|
53
|
|
Exploiting Gene Expression Profiles for the Automated Prediction of Connectivity between Brain Regions, file e384c431-2c22-d4b2-e053-9f05fe0a1d67
|
50
|
|
isomiR-SEA: An RNA-Seq analysis tool for miRNAs/isomiRs expression level profiling and miRNA-mRNA interaction sites evaluation, file e384c432-f223-d4b2-e053-9f05fe0a1d67
|
45
|
|
Cytoarchitectural analysis of the neuron-to-glia association in the dorsal root ganglia of normal and diabetic mice, file e384c432-7175-d4b2-e053-9f05fe0a1d67
|
40
|
|
Novel and Rare Fusion Transcripts Involving Transcription Factors and Tumor Suppressor Genes in Acute Myeloid Leukemia, file e384c431-bcd3-d4b2-e053-9f05fe0a1d67
|
38
|
|
Going Deeper into Colorectal Cancer Histopathology, file e384c431-e5a3-d4b2-e053-9f05fe0a1d67
|
38
|
|
Dealing with Lack of Training Data for Convolutional Neural Networks: The Case of Digital Pathology, file e384c431-7406-d4b2-e053-9f05fe0a1d67
|
37
|
|
BioSeqZip: a collapser of NGS redundant reads for the optimisation of sequence analysis, file e384c431-96da-d4b2-e053-9f05fe0a1d67
|
35
|
|
PhyliCS: a Python library to explore scCNA data and quantify spatial tumor heterogeneity, file e384c433-dcd4-d4b2-e053-9f05fe0a1d67
|
32
|
|
isomiR-SEA: miRNA and isomiR expression level detection in seven RNA-Seq datasets, file e384c431-b2f6-d4b2-e053-9f05fe0a1d67
|
25
|
|
Unification of miRNA and isomiR research: the mirGFF3 format and the mirtop API, file e384c431-9243-d4b2-e053-9f05fe0a1d67
|
24
|
|
Aneuploid acute myeloid leukemia exhibits a signature of genomic alterations in the cell cycle and protein degradation machinery, file e384c431-88b0-d4b2-e053-9f05fe0a1d67
|
20
|
|
Automated 3D immunofluorescence analysis of Dorsal Root Ganglia for the investigation of neural circuit alterations: a preliminary study., file e384c431-906d-d4b2-e053-9f05fe0a1d67
|
18
|
|
Predicting the oncogenic potential of gene fusions using convolutional neural networks, file e384c431-91d5-d4b2-e053-9f05fe0a1d67
|
17
|
|
A multi-modal brain image registration framework for US-guided neuronavigation systems. Integrating MR and US for minimally invasive neuroimaging., file e384c431-72aa-d4b2-e053-9f05fe0a1d67
|
14
|
|
W2WNet: A two-module probabilistic Convolutional Neural Network with embedded data cleansing functionality, file 5039feca-a4f8-4783-8c90-3494a8085fcb
|
11
|
|
Single-cell DNA Sequencing Data: a Pipeline for Multi-Sample Analysis, file e384c431-11f4-d4b2-e053-9f05fe0a1d67
|
11
|
|
A Novel Proof-of-concept Framework for the Exploitation of ConvNets on Whole Slide Images, file e384c433-5958-d4b2-e053-9f05fe0a1d67
|
11
|
|
A survey on data integration for multi-omics sample clustering, file e384c434-c5af-d4b2-e053-9f05fe0a1d67
|
7
|
|
geneEX a novel tool to assess differential expression from gene and exon sequencing data, file e384c431-9231-d4b2-e053-9f05fe0a1d67
|
5
|
|
Optimizing Quality Inspection and Control in Powder Bed Metal Additive Manufacturing: Challenges and Research Directions, file e384c433-0145-d4b2-e053-9f05fe0a1d67
|
5
|
|
LaRA 2: parallel and vectorized program for sequence–structure alignment of RNA sequences, file e384c434-b828-d4b2-e053-9f05fe0a1d67
|
5
|
|
Predicting the oncogenic potential of gene fusions using convolutional neural networks, file e384c431-91d4-d4b2-e053-9f05fe0a1d67
|
4
|
|
ANAlyte: a modular image analysis tool for ANA testing with Indirect Immunofluorescence, file e384c431-9d60-d4b2-e053-9f05fe0a1d67
|
4
|
|
Identifying the oncogenic potential of gene fusions exploiting miRNAs, file 38e3408e-7680-4db8-b3f3-e5f68079ef87
|
3
|
|
Subclass Discriminant Analysis of Morphological and Textural Features for HEp-2 Staining Pattern Classification, file e384c42e-a324-d4b2-e053-9f05fe0a1d67
|
3
|
|
Colorectal Cancer Classification using Deep Convolutional Networks. An Experimental Study, file e384c431-7d70-d4b2-e053-9f05fe0a1d67
|
3
|
|
An automated approach to the segmentation of HEp-2 cells for the indirect immunofluorescence ANA test, file e384c431-8a89-d4b2-e053-9f05fe0a1d67
|
3
|
|
Convergent Mutations and Kinase Fusions Lead to Oncogenic STAT3 Activation in Anaplastic Large Cell Lymphoma, file e384c431-950b-d4b2-e053-9f05fe0a1d67
|
3
|
|
A multi-modal brain image registration framework for US-guided neuronavigation systems. Integrating MR and US for minimally invasive neuroimaging., file e384c431-9c52-d4b2-e053-9f05fe0a1d67
|
3
|
|
Cytoarchitectural analysis of the neuron-to-glia association in the dorsal root ganglia of normal and diabetic mice, file e384c432-46f4-d4b2-e053-9f05fe0a1d67
|
3
|
|
Unsupervised Multi-Omic Data Fusion: the Neural Graph Learning Network, file e384c432-76a4-d4b2-e053-9f05fe0a1d67
|
3
|
|
W2WNet: A two-module probabilistic Convolutional Neural Network with embedded data cleansing functionality, file 4d2d5fc7-e4ed-4b5b-ab66-b14bd86ab218
|
2
|
|
Bellerophontes: a RNA-seq data analysis framework tor chimeric transcripts discovery base on accurate fusion model, file e384c42e-a668-d4b2-e053-9f05fe0a1d67
|
2
|
|
A novel patient-derived tumorgraft model with TRAF1-ALK
anaplastic large-cell lymphoma translocation, file e384c431-8080-d4b2-e053-9f05fe0a1d67
|
2
|
|
Unification of miRNA and isomiR research: the mirGFF3 format and the mirtop API, file e384c431-b358-d4b2-e053-9f05fe0a1d67
|
2
|
|
A Novel Proof-of-concept Framework for the Exploitation of ConvNets on Whole Slide Images, file e384c433-826d-d4b2-e053-9f05fe0a1d67
|
2
|
|
FunMod: A Cytoscape Plugin for Identifying Functional Modules in Undirected Protein–Protein Networks, file e384c42f-20ad-d4b2-e053-9f05fe0a1d67
|
1
|
|
FunMod: A Cytoscape Plugin for Identifying Functional Modules in Undirected Protein–Protein Networks, file e384c42f-2437-d4b2-e053-9f05fe0a1d67
|
1
|
|
Going Deeper into Colorectal Cancer Histopathology, file e384c431-e5a7-d4b2-e053-9f05fe0a1d67
|
1
|
|
Exploration of Convolutional Neural Network models for source code classification, file e384c432-a14e-d4b2-e053-9f05fe0a1d67
|
1
|
|
Unsupervised Multi-Omic Data Fusion: the Neural Graph Learning Network, file e384c432-c82c-d4b2-e053-9f05fe0a1d67
|
1
|
| Totale |
22.894 |
Archivio Istituzionale della Ricerca