Application of parameter optimization to molecular comparison (2008)
C. Lemmen, A. Zien, R. Zimmer, T. Lengauer
problems
A. Zien, G. Rätsch, S. Mika, B. Schölkopf, T. Lengauer
Motivation: In order to extract protein sequences from nucleotide sequences, it is an important step to recognize points at which regions start that code for proteins. These points are called...
A. Zien, G. Rätsch, S. Mika, B. Schölkopf, C. Lemmen, A. Smola
Abstract In order to extract protein sequences from nucleotide sequences, it is an important step to recognize points from which regions encoding proteins start, the so-called translation initiation...
Sonnenburg, S., Zien, A., Philips, P., Rätsch, G.
Motivation: At the heart of many important bioinformatics problems, such as gene finding and function prediction, is the classification of biological sequences. Frequently the most accurate...
An Automated Combination of Kernels for Predicting Protein Subcellular Localization (2008)
Ong, C.S., Zien, A., Crandall, K. A., Lagergren, J.
Protein subcellular localization is a crucial ingredient to many important inferences about cellular processes, including prediction of protein function and protein interactions. While many...
Phenotyping of Chondrocytes In Vivo and In Vitro Using cDNA Array Technology (2007)
Zien, A., Gebhard, P.M., Fundel, K., Aigner, T.
The cDNA array technology is a powerful tool to analyze a high number of genes in parallel. We investigated whether large-scale gene expression analysis allows clustering and identification of...
Transductive Support Vector Machines for Structured Variables (2007)
Zien, A., Brefeld, U., Scheffer, T.
We study the problem of learning kernel machines transductively for structured output variables. Transductive learning can be reduced to combinatorial optimization problems over all possible...
Training and Approximation of a Primal Multiclass Support Vector Machine (2007)
We revisit the multiclass support vector machine (SVM) and generalize the formulation to convex loss functions and joint feature maps. Motivated by recent work [Chapelle, 2006] we use logistic loss...
Multiclass Multiple Kernel Learning (2007)
In many applications it is desirable to learn from several kernels. Multiple kernel learning (MKL) allows the practitioner to optimize over linear combinations of kernels. By enforcing sparse...
ARTS: Accurate Recognition of Transcription Starts in Human (2006)
Sonnenburg, S., Zien, A., Rätsch, G.
Motivation: One of the most important features of genomic DNA are the protein-coding genes. While it is of great value to identify those genes and the encoded proteins, it is also crucial to...
A Continuation Method for Semi-Supervised SVMs (2006)
Chapelle, O., Chi, M., Zien, A.
Semi-Supervised Support Vector Machines (S3VMs) are an appealing method for using unlabeled data in classification: their objective function favors decision boundaries which do not cut clusters....
Aigner, T., Fundel, K., Saas, J., Gebhard, P.M., Haag, J., Weiss, T., ...
Objective. Despite many research efforts in recent decades, the major pathogenetic mechanisms of osteo- arthritis (OA), including gene alterations occurring during OA cartilage degeneration, are...
Semi-Supervised Learning (2006)
Chapelle, O., Schölkopf, B., Zien, A.
In the field of machine learning, semi-supervised learning (SSL) occupies the middle ground, between supervised learning (in which all training examples are labeled) and unsupervised learning (in...
ARTS: Accurate Recognition of Transcription Starts in Human (2006)
Sonnenburg, S., Zien, A., Rätsch, G.
We develop new methods for finding transcription start sites (TSS) of RNA Polymerase II binding genes in genomic DNA sequences. Employing Support Vector Machines with advanced sequence kernels, we...
Semi-Supervised Classification by Low Density Separation (2005)
We believe that the cluster assumption is key to successful semi-supervised learning. Based on this, we propose three semi-supervised algorithms: 1. deriving graph-based distances that emphazise low...
Phenotypic characterization of chondrosarcoma-derived cell lines (2005)
Schorle, C., Finger, F., Zien, A., Block, J., Gebhard, P., Aigner, T.
Gene expression profiling of three chondrosarcoma derived cell lines (AD, SM, 105KC) showed an increased proliferative activity and a reduced expression of chondrocytic-typical matrix products...
Large Margin Non-Linear Embedding (2005)
Zien, A., Candela, J., Raedt, L. De, Wrobel, S.
It is common in classification methods to first place data in a vector space and then learn decision boundaries. We propose reversing that process: for fixed decision boundaries, we...
Learning to Find Graph Pre-Images (2004)
The recent development of graph kernel functions has made it possible to apply well-established machine learning methods to graphs. However, to allow for analyses that yield a graph as a result, it...
Prediction on Spike Data Using Kernel Algorithms (2004)
Eichhorn,J., Tolias,A.S., Zien,A., Kuss,M., Rasmussen,C.E., Weston,J., ...
We report and compare the performance of different learning algorithms based on data from cortical recordings. The task is to predict the orientation of visual stimuli from the activity of a...
Finger,F., Schörle,C., Söder,S., Zien,A., Goldring,M.B., Aigner,T.
DNA microarray analysis was used to investigate the molecular phenotype of one of the first human chondrocyte cell lines, C-20/A4, derived from juvenile costal chondrocytes by immortalization with...
Aigner,T., Finger,F., Zien,A., Bartnik,E.
Functional genomics represents a new challenging approach in order to analyze complex diseases such as osteoarthritis on a molecular level. The characterization of the molecular changes of the...
A primer on molecular biology (2004)
Zien, A., Schoelkopf, B., Tsuda, K., Vert, J. P.
Modern molecular biology provides a rich source of challenging machine learning problems. This tutorial chapter aims to provide the necessary biological background knowledge required to communicate...
Prediction on Spike Data Using Kernel Algorithms (2004)
Eichhorn, J., Tolias, A.S., Zien, A., Kuss, M., Rasmussen, C.E., Weston, J., ...
We report and compare the performance of different learning algorithms based on data from cortical recordings. The task is to predict the orientation of visual stimuli from the activity of a...
Learning to Find Graph Pre-Images (2004)
Bakir, G.H., Zien, A., Tsuda, K., Rasmussen, C. E., Buelthoff, H. H., Giese, M. A., ...
The recent development of graph kernel functions has made it possible to apply well-established machine learning methods to graphs. However, to allow for analyses that yield a graph as a result, it...
Finger, F., Schörle, C., Söder, S., Zien, A., Goldring, M.B., Aigner, T.
DNA microarray analysis was used to investigate the molecular phenotype of one of the first human chondrocyte cell lines, C-20/A4, derived from juvenile costal chondrocytes by immortalization with...
Aigner, T., Finger, F., Zien, A., Bartnik, E.
Functional genomics represents a new challenging approach in order to analyze complex diseases such as osteoarthritis on a molecular level. The characterization of the molecular changes of the...
Microarrays: How Many Do You Need? (2003)
Zien, A., Fluck, J., Zimmer, R., Lengauer, T.
We estimate the number of microarrays that is required in order to gain reliable results from a common type of study: the pairwise comparison of different classes of samples. We show that current...
Becker, A., Chen, J., Zien, A., Sochivko, D., Normann, S., Schramm, J., ...
Knorr, T., Obermayr, F., Bartnik, E., Zien, A., Aigner, T.
Objective: To investigate quantitatively the mRNA expression levels of YKL-40, an established marker of rheumatoid and osteoarthritic cartilage degeneration in synovial fluid and serum, and a closely...
Molecular phenotyping of human chondrocyte cell lines T/C-28a2, T/C-28a4, and C-28/I2 (2003)
Finger, F., Schörle, C., Zien, A., Gebhard, P., Goldring, M.B., Aigner, T.
Objective. Because the immortalized chondrocyte cell lines C-28/I2, T/C-28a2, and T/C-28a4 have become a common tool in cartilage research, permitting investigations in a largely unlimited and...
Confidence measures for protein fold recognition (2002)
Sommer, I., Zien, A., Öhsen, N. Von, Zimmer, R., Lengauer, T.
Motivation: We present an extensive evaluation of different methods and criteria to detect remote homologs of a given protein sequence. We investigate two associated problems: first, to develop a...
Functional genomics of osteoarthritis (2002)
Aigner, T., Bartnik, E., Zien, A., Zimmer, R.
Functional genomics is a challenging new way to address a complex disease like osteoarthritis on a molecular level. Despite osteoarthritis being ultimately a biochemical problem, mainly characterized...
Identification of Drug Target Proteins (2000)
Zien, A., Küffner, R., Mevissen, T., Zimmer, R., Lengauer, T.
Engineering support vector machine kernels that recognize translation initiation sites (2000)
Zien, A., Rätsch, G., Mika, S., Schölkopf, B., Lengauer, T.
Motivation: In order to extract protein sequences from nucleotide sequences, it is an important step to recognize points at which regions start that code for proteins. These points are called...
Engineering Support Vector Machine Kernels That Recognize Translation Initiation Sites (2000)
A. Zien, G. Rätsch, S. Mika, B. Schölkopf, T. Lengauer
Motivation: In order to extract protein sequences from nucleotide sequences, it is an important step to recognize points at which regions start that code for proteins. These points are called...
Engineering support vector machine kernels that recognize translation initiation sites (2000)
Zien, A., Rätsch, G., Mika, S., Schölkopf, B., Lengauer, T.
Motivation: In order to extract protein sequences from nucleotide sequences, it is an important step to recognize points at which regions start that code for proteins. These points are called...
Zien, A., Rätsch, G., Mika, S., Schölkopf, B., Lemmen, C., Smola, A.J., ...
Knorr, T, Obermayr, F, Bartnik, E, Zien, A, Aigner, T
Methods: cDNA array and online quantitative polymerase chain reaction (PCR) were used to measure mRNA expression levels of YKL-39 and YKL-40 in chondrocytes in normal, early degenerative, and late...