All Stories

  1. Cell type identification via convolutional neural networks and self-organizing maps on single-cell RNA-seq data
  2. Deep Learning Approach for Breast Cancer InClust 5 Prediction based on Multiomics Data Integration
  3. iSOM-GSN
  4. A Gene-disease-based Machine Learning Approach to Identify Prostate Cancer Biomarkers
  5. A Deep Learning Model to Identify a Genomic Signature Driving Sporadic Colorectal Cancer in Young Adults
  6. A Machine Learning Model for Discovery of Protein Isoforms as Biomarkers
  7. Prediction of hormone and chemotherapy in breast cancer
  8. Cost-sensitive classification on class-balanced ensembles for imbalanced non-coding RNA data
  9. A new clustering method using wavelet based probability density functions for identifying patterns in time-series data
  10. Structural Domains in Prediction of Biological Protein-Protein Interactions
  11. ZSeq 2.0: A fully automatic preprocessing method for next generation sequencing data
  12. Obtaining biomarkers in cancer progression from outliers of time-series clusters
  13. A new compact set of biomarkers for distinguishing among ten breast cancer subtypes
  14. Classification via correlation-based feature grouping
  15. A novel approach for finding informative genes in ten subtypes of breast cancer
  16. Prediction of high-throughput protein-protein interactions based on protein sequence information
  17. Pattern classification using a new border identification paradigm: The nearest border technique
  18. A Computational Domain-Based Feature Grouping Approach for Prediction of Stability of SCF Ligases
  19. Breast cancer subtype identification using machine learning techniques
  20. A new multi-level thresholding algorithm for finding peaks in ChIP-Seq data
  21. A model based on minimotifs for classification of stable protein-protein complexes
  22. CMT: A Constrained Multi-Level Thresholding Approach for ChIP-Seq Data Analysis
  23. Computational analysis of the stability of SCF ligases employing domain information
  24. Using desolvation energies of structural domains to predict stability of protein complexes
  25. A New Paradigm for Pattern Classification: Nearest Border Techniques
  26. Identifying Informative Genes for Prediction of Breast Cancer Subtypes
  27. MicroRNA identification using linear dimensionality reduction with explicit feature mapping
  28. The role of electrostatic energy in prediction of obligate protein-protein interactions
  29. A model to predict and analyze protein-protein interaction types using electrostatic energies
  30. Finding genomic features from enriched regions in ChlP-Seq data
  31. Prediction of crystal packing and biological protein-protein interactions
  32. Using structural domains to predict obligate and non-obligate protein-protein interactions
  33. A Framework of Gene Subset Selection Using Multiobjective Evolutionary Algorithm
  34. A new algorithm for finding enriched regions in ChIP-Seq data
  35. Multi-level structural domain-domain interactions for prediction of obligate and non-obligate protein-protein interactions
  36. A Novel Recursive Feature Subset Selection Algorithm
  37. Prediction of biological protein-protein interactions using atom-type and amino acid properties
  38. Biofilm Image Analysis
  39. Alignment-Based Clustering of Gene Expression Time-Series Data
  40. Image segmentation of biofilm structures using optimal multi-level thresholding
  41. A fully automatic gridding method for cDNA microarray images
  42. New Gene Subset Selection Approaches Based on Linear Separating Genes and Gene-Pairs
  43. Applications of Multilevel Thresholding Algorithms to Transcriptomics Data
  44. Biological assessment of grid and spot detection in cDNA microarray images
  45. Analysis of obligate and non-obligate complexes using desolvation energies in domain-domain interactions
  46. A parameterless automatic spot detection method for cDNA microarray images
  47. Protein-protein interaction prediction using desolvation energies and interface properties
  48. Selection based heuristics for the non-unique oligonucleotide probe selection problem in microarray design
  49. Alignment versus variation methods for clustering microarray time-series data
  50. Multi-class pairwise linear dimensionality reduction using heteroscedastic schemes
  51. Missing value imputation methods for gene-sample-time microarray data analysis
  52. New approaches to clustering microarray time-series data using multiple expression profile alignment
  53. Biofilm growth kinetics of a monomethylamine producing Alphaproteobacteria strain isolated from an anaerobic reactor
  54. Sub-grid and Spot Detection in DNA Microarray Images Using Optimal Multi-level Thresholding
  55. Alignment-based versus variation-based transformation methods for clustering microarray time-series data
  56. Biofilm Image Segmentation Using Optimal Multi-level Thresholding
  57. Clustering microarray time-series data using expectation maximization and multiple profile alignment
  58. A Pattern Classification Approach to DNA Microarray Image Segmentation
  59. An Evolutionary Approach for Correcting Random Amplified Polymorphism DNA Images
  60. Microarray Time-Series Data Clustering via Multiple Alignment of Gene Expression Profiles
  61. Efficient Optimal Multi-level Thresholding for Biofilm Image Segmentation
  62. A theoretical comparison of two-class Fisher’s and heteroscedastic linear dimensionality reduction schemes
  63. Linear dimensionality reduction by maximizing the Chernoff distance in the transformed space
  64. An efficient compression scheme for data communication which uses a new family of self-organizing binary search trees
  65. Evolution strategy with greedy probe selection heuristics for the non-unique oligonucleotide probe selection problem
  66. An Efficient Algorithm for Optimal Multilevel Thresholding of Irregularly Sampled Histograms
  67. An Evolutionary Approach to the Non-unique Oligonucleotide Probe Selection Problem
  68. Clustering Time-Series Gene Expression Data with Unequal Time Intervals
  69. Clustering temporal gene expression data with unequal time intervals
  70. A new approach to adaptive encoding data using self-organizing data structures
  71. Advances in Image and Video Technology
  72. Progress in Pattern Recognition, Image Analysis and Applications
  73. Prediction of Biological Protein-protein Interaction Types Using Short-Linear Motifs
  74. Clustering Temporal Gene Expression Data with Unequal Time Intervals
  75. Geometric visualization of clusters obtained from fuzzy clustering algorithms
  76. Stochastic learning-based weak estimation of multinomial random variables and its applications to pattern recognition in non-stationary environments
  77. A New Profile Alignment Method for Clustering Gene Expression Data
  78. Toward New Paradigms to Combating Internet Child Pornography
  79. A Theoretical Comparison of Two Linear Dimensionality Reduction Techniques
  80. A New Approach to Multi-class Linear Dimensionality Reduction
  81. A New Linear Dimensionality Reduction Technique Based on Chernoff Distance
  82. On the Performance of Chernoff-Distance-Based Linear Dimensionality Reduction Techniques
  83. A one-dimensional analysis for the probability of error of linear classifiers for normally distributed classes
  84. A formal analysis of why heuristic functions work
  85. A New Approach to Automatically Detecting Grids in DNA Microarray Images
  86. A New Method for DNA Microarray Image Segmentation
  87. Spot Detection and Image Segmentation in DNA??Microarray Data
  88. Fast Protein Superfamily Classification Using Principal Component Null Space Analysis
  89. Efficient Adaptive Data Compression Using Fano Binary Search Trees
  90. On Utilizing Stochastic Learning Weak Estimators for Training and Classification of Patterns with Non-stationary Distributions
  91. An efficient approach to compute the threshold for multi-dimensional linear classifiers
  92. A nearly-optimal Fano-based coding algorithm
  93. An Improved Clustering-Based Approach for DNA Microarray Image Segmentation
  94. Selecting the best hyperplane in the framework of optimal pairwise linear classifiers
  95. A New Family of Weak Estimators for Training in Non-stationary Distributions
  96. New Bounds and Approximations for the Error of Linear Classifiers
  97. On Families of New Adaptive Compression Algorithms Suitable for Time-Varying Source Data
  98. On optimal pairwise linear classifiers for normal distributions: the d-dimensional case
  99. A New Approach That Selects a Single Hyperplane from the Optimal Pairwise Linear Classifier
  100. Resolving Minsky’s Paradox : The d-Dimensional Normal Distribution Case
  101. The Foundational Theory of Optimal Bayesian Pairwise Linear Classifiers
  102. Sub-grid Detection in DNA Microarray Images
  103. Stochastic Learning-based Weak Estimation and Its Applications
  104. Processing Random Amplified Polymorphysm DNA Images Using the Radon Transform and Mathematical Morphology
  105. Chernoff-Based Multi-class Pairwise Linear Dimensionality Reduction
  106. Sequential Forward Selection Approach to the Non-unique Oligonucleotide Probe Selection Problem