Schliep, Alexander.
Alexander Schliep researcher
VIAF ID: 120520297 (Personal)
Permalink: http://viaf.org/viaf/120520297
Preferred Forms
- 100 0 _ ‡a Alexander Schliep ‡c researcher
- 100 1 _ ‡a Schliep, Alexander
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- 100 1 _ ‡a Schliep, Alexander
- 100 1 _ ‡a Schliep, Alexander
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- 100 1 _ ‡a Schliep, Alexander
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4xx's: Alternate Name Forms (1)
Works
Title | Sources |
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Automatic learning of pre-miRNAs from different species | |
Bayesian approach to learning Hidden Markov model topology with applications to biological sequence analysis | |
CATBox, 2009: | |
CATBox : an interactive course in combinatorial optimization | |
Classifying short gene expression time-courses with Bayesian estimation of piecewise constant functions | |
CLEVER: clique-enumerating variant finder | |
Clustering cancer gene expression data: a comparative study | |
Constrained mixture estimation for analysis and robust classification of clinical time series | |
Context-specific independence mixture modeling for positional weight matrices | |
Decoding non-unique oligonucleotide hybridization experiments of targets related by a phylogenetic tree | |
Developing Gato and CATBox with Python: Teaching Graph Algorithms through Visualization and Experimentation | |
The discriminant power of RNA features for pre-miRNA recognition | |
Efficient algorithms for the computational design of optimal tiling arrays | |
Embracing heterogeneity: coalescing the Tree of Life and the future of phylogenomics | |
Fast MCMC sampling for hidden Markov Models to determine copy number variations | |
Gene expression trees in lymphoid development | |
Identifying protein complexes directly from high-throughput TAP data with Markov random fields | |
Indel-tolerant read mapping with trinucleotide frequencies using cache-oblivious kd-trees | |
An Indicator for the Number of Clusters: Using a Linear Map to Simplex Structure | |
Inferring differentiation pathways from gene expression | |
Joint Analysis of In-situ Hybridization and Gene Expression Data | |
Model-Based Clustering With Hidden Markov Models and its Application to Financial Time-Series Data | |
A new Algorithm for Accelerating Pair-Wise Computations of Melting Temperature | |
New, improved, and practical k-stem sequence similarity measures for probe design. | |
On External Indices for Mixtures: Validating Mixtures of Genes | |
Optimal robust non-unique probe selection using Integer Linear Programming. | |
Partially-supervised protein subclass discovery with simultaneous annotation of functional residues | |
pGQL: A probabilistic graphical query language for gene expression time courses | |
ProClust: improved clustering of protein sequences with an extended graph-based approach. | |
PyMix--the python mixture package--a tool for clustering of heterogeneous biological data | |
Ranking and selecting clustering algorithms using a meta-learning approach | |
Robust inference of groups in gene expression time-courses using mixtures of HMMs. | |
Selecting oligonucleotide probes for whole-genome tiling arrays with a cross-hybridization potential | |
Selecting signature oligonucleotides to identify organisms using DNA arrays. | |
Semi-supervised learning for the identification of syn-expressed genes from fused microarray and in situ image data | |
Single cell genome analysis of an uncultured heterotrophic stramenopile. | |
SLIQ: simple linear inequalities for efficient contig scaffolding | |
Speeding Up Bayesian HMM by the Four Russians Method | |
Strongly Connected Components can Predict Protein Structure | |
Turtle: identifying frequent k-mers with cache-efficient algorithms | |
Using hidden Markov models to analyze gene expression time course data |