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Kay Hofmann

dblp:80/2569 · DBLP profile ↗
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4ranked-venue papers
1as first author
0since 2021 · last 2005
0000-0002-2289-9083ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 4 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › sequence alignment
alignment scoring
0.011996
A Sequence Similarity Search Algorithm Based on a Probabilistic Interpretation of an Alignment Scoring System · ISMB 1996
Bioinformatics and computational biology › sequence analysis
sequence similarity search
0.011996
A Sequence Similarity Search Algorithm Based on a Probabilistic Interpretation of an Alignment Scoring System · ISMB 1996
YearPublicationVenuePosition
2005 Prediction of a common structural scaffold for proteasome lid, COP9-signalosome and eIF3 complexes
abstract
BACKGROUND: The 'lid' subcomplex of the 26S proteasome and the COP9 signalosome (CSN complex) share a common architecture consisting of six subunits harbouring a so-called PCI domain (proteasome, CSN, eIF3) at their C-terminus, plus two subunits containing MPN domains (Mpr1/Pad1 N-terminal). The translation initiation complex eIF3 also contains PCI- and MPN-domain proteins, but seems to deviate from the 6+2 stoichiometry. Initially, the PCI domain was defined as the region of detectable sequence similarity between the components mentioned above. RESULTS: During an exhaustive bioinformatical analysis of proteasome components, we detected multiple instances of tetratrico-peptide repeats (TPR) in the N-terminal region of most PCI proteins, suggesting that their homology is not restricted to the PCI domain. We also detected a previously unrecognized PCI domain in the eIF3 component eIF3k, a protein whose 3D-structure has been determined recently. By using profile-guided alignment techniques, we show that the structural elements found in eIF3k are most likely conserved in all PCI proteins, resulting in a structural model for the canonical PCI domain. CONCLUSION: Our model predicts that the homology domain PCI is not a true domain in the structural sense but rather consists of two subdomains: a C-terminal 'winged helix' domain with a key role in PCI:PCI interaction, preceded by a helical repeat region. The TPR-like repeats detected in the N-terminal region of PCI proteins most likely form an uninterrupted extension of the repeats found within the PCI domain boundaries. This model allows an interpretation of several puzzling experimental results.
Hartmut Scheel, Kay Hofmann
BMC Bioinform.2
2001 Microarray Probe Selection Strategies
abstract
During recent years, DNA microarrays have become the method of choice to monitor the expression level of a large number of genes. Depending on the focus of the study and the method of microarray fabrication, a number of different strategies for probe selection may be most appropriate. One consideration concerns the length of the probe, ranging from some 25 residues used for oligonucleotide arrays to complete cDNAs. Unless resources are truly unlimited, an important decision to be made is the amount of effort to be put into the selection of genes and gene fragments. While high-throughput cDNA arraying projects usually will select from a collection of existing cDNA clones, smaller projects focusing on a number of selected genes can afford to selectively amplify fragments optimised for that purpose. This paper discusses the full scope of probe selection strategies, highlighting the problems that may be encountered in the various systems.
Stefan Tomiuk, Kay Hofmann
Briefings Bioinform.2
2000 Sensitive Protein Comparisons with Profiles and Hidden Markov Models
abstract
Sequence database searches have become an important tool for the life sciences in general and for gene discovery-driven biotechnology in particular. Both the functional assignment of newly found proteins and the mining of genome databases for functional candidates are equally important tasks typically addressed by database searches. Sensitivity and reliability of the search methods are of crucial importance. The overall performance of sequence alignments and database searches can be enhanced considerably, when profiles or hidden Markov models (HMMs) derived from protein families are used as query objects instead of single sequences. This review discusses the concept of profiles, generalised profiles and profile-HMMs, the methods how they are constructed and the scope of possible applications in gene discovery and gene functional assignment.
Kay Hofmann
Briefings Bioinform.1
1996 A Sequence Similarity Search Algorithm Based on a Probabilistic Interpretation of an Alignment Scoring System
Philipp Bucher, Kay Hofmann
ISMB2