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Ketil Malde

dblp:99/3869 · DBLP profile ↗
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11ranked-venue papers
7as first author
0since 2021 · last 2013
0000-0001-7381-1849ORCID · corroborated

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

Applied, interdisciplinary, general and emerging computing · 9 · 5 first-authorSoftware engineering, systems software and programming languages · 2 · 2 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
8 papers
Bioinformatics and computational biology · 100%

Topics — the 14 heaviest of 15, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › sequence analysis
sequencing data processing
0.432013
Filtering duplicate reads from 454 pyrosequencing data · Bioinform. 2013
Flower: extracting information from pyrosequencing data · Bioinform. 2011
Systematic exploration of error sources in pyrosequencing flowgram data · Bioinform. 2011
Bioinformatics and computational biology › sequence analysis › sequencing read preprocessing
duplicate read removal
0.212013
Filtering duplicate reads from 454 pyrosequencing data · Bioinform. 2013
Bioinformatics and computational biology
sequence analysis
0.132010
Characteristics of 454 pyrosequencing data - enabling realistic simulation with flowsim · Bioinform. 2010
The effect of sequence quality on sequence alignment · Bioinform. 2008
Fast Sequence Clustering Using A Suffix Array Algorithm · Bioinform. 2003
Bioinformatics and computational biology › next-generation sequencing
next-generation sequencing simulation
0.112010
Characteristics of 454 pyrosequencing data - enabling realistic simulation with flowsim · Bioinform. 2010
Bioinformatics and computational biology › sequence analysis
sequence clustering
0.122006
RBR: library-less repeat detection for ESTs · Bioinform. 2006
Fast Sequence Clustering Using A Suffix Array Algorithm · Bioinform. 2003
Bioinformatics and computational biology
sequence alignment
0.112008
The effect of sequence quality on sequence alignment · Bioinform. 2008
Bioinformatics and computational biology › genome annotation
repeat masking
0.112006
RBR: library-less repeat detection for ESTs · Bioinform. 2006
Bioinformatics and computational biology › sequence analysis
sequence assembly
0.112005
A graph based algorithm for generating EST consensus sequences · Bioinform. 2005
Bioinformatics and computational biology › sequence analysis › sequence clustering
EST clustering
0.012003
Fast Sequence Clustering Using A Suffix Array Algorithm · Bioinform. 2003
Bioinformatics and computational biology
metagenomics
0.012011
Flower: extracting information from pyrosequencing data · Bioinform. 2011
Bioinformatics and computational biology › sequence analysis › sequence assembly › genome assembly
assembly quality assessment
0.012010
Characteristics of 454 pyrosequencing data - enabling realistic simulation with flowsim · Bioinform. 2010
Bioinformatics and computational biology › sequence analysis › sequence assembly
genome assembly
0.012010
Characteristics of 454 pyrosequencing data - enabling realistic simulation with flowsim · Bioinform. 2010
Bioinformatics and computational biology › transcriptomics
expressed sequence tag analysis
0.012006
RBR: library-less repeat detection for ESTs · Bioinform. 2006
Bioinformatics and computational biology › transcriptomics
transcript assembly
0.012005
A graph based algorithm for generating EST consensus sequences · Bioinform. 2005

Methods — techniques the papers use, named apart from their topics

simulation · 0.2read clustering · 0.2bayesian distance measures · 0.2file format parsing · 0.1empirical distribution modeling · 0.1dynamic programming · 0.1BLAST · 0.1match statistics · 0.1graph-based assembly · 0.1suffix array · 0.0
YearPublicationVenuePosition
2013 Filtering duplicate reads from 454 pyrosequencing data
abstract
MOTIVATION: Throughout the recent years, 454 pyrosequencing has emerged as an efficient alternative to traditional Sanger sequencing and is widely used in both de novo whole-genome sequencing and metagenomics. Especially the latter application is extremely sensitive to sequencing errors and artificially duplicated reads. Both are common in 454 pyrosequencing and can create a strong bias in the estimation of diversity and composition of a sample. To date, there are several tools that aim to remove both sequencing noise and duplicates. Nevertheless, duplicate removal is often based on nucleotide sequences rather than on the underlying flow values, which contain additional information. RESULTS: With the novel tool JATAC, we present an approach towards a more accurate duplicate removal by analysing flow values directly. Making use of previous findings on 454 flow data characteristics, we combine read clustering with Bayesian distance measures. Finally, we provide a benchmark with an existing algorithm. AVAILABILITY: JATAC is freely available under the General Public License from http://malde.org/ketil/jatac/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Susanne Balzer, Ketil Malde, Markus A. Grohme, Inge Jonassen
Bioinform.2
2011 Systematic exploration of error sources in pyrosequencing flowgram data
abstract
MOTIVATION: 454 pyrosequencing, by Roche Diagnostics, has emerged as an alternative to Sanger sequencing when it comes to read lengths, performance and cost, but shows higher per-base error rates. Although there are several tools available for noise removal, targeting different application fields, data interpretation would benefit from a better understanding of the different error types. RESULTS: By exploring 454 raw data, we quantify to what extent different factors account for sequencing errors. In addition to the well-known homopolymer length inaccuracies, we have identified errors likely to originate from other stages of the sequencing process. We use our findings to extend the flowsim pipeline with functionalities to simulate these errors, and thus enable a more realistic simulation of 454 pyrosequencing data with flowsim. AVAILABILITY: The flowsim pipeline is freely available under the General Public License from http://biohaskell.org/Applications/FlowSim. CONTACT: [email protected].
Susanne Balzer, Ketil Malde, Inge Jonassen
Bioinform.2
2011 Characteristics of 454 pyrosequencing data - enabling realistic simulation with flowsim
abstract
Bioinformatics (2010) 26(18), i420–i425. The authors would like to apologize for an error in the calculation of the number of bases, number of flow values and average read length. Our reads turned out to be a lot shorter than previously reported. None of these errors has implications on the method or the results. The corrected table is shown below. Data basis for building the empirical distributions aAfter 454 quality-trimming. bWithout N's. cHomopolymer lengths 1–5, equals to number of homopolymer runs in BLAST results. The error also affects Figure 1b, where the left part of the plot is to be compared with the right set of curves. The corrected figure is shown below. (b) Absolute frequencies of flow values (E.coli). Left: original data, no quality-trimming; right: quality-trimmed. The trimming algorithm enhances the separation of the homopolymer length distributions and levels out discrepancies between the nucleotides such that the curves for the four nucleotides are nearly identical.
Susanne Balzer, Ketil Malde, Anders Lanzén, Animesh Sharma, Inge Jonassen
Bioinform.2
2011 Flower: extracting information from pyrosequencing data
abstract
UNLABELLED: The SFF file format produced by Roche's 454 sequencing technology is a compact, binary format that contains the flow values that are used for base and quality calling of the reads. Applications, e.g. in metagenomics, often depend on accurate sequence information, and access to flow values is important to estimate the probability of errors. Unfortunately, the programs supplied by Roche for accessing this information are not publicly available. Flower is a program that can extract the information contained in SFF files, and convert it to various textual output formats. AVAILABILITY: Flower is freely available under the General Public License.
Ketil Malde
Bioinform.1
2010 Characteristics of 454 pyrosequencing data - enabling realistic simulation with flowsim
abstract
MOTIVATION: The commercial launch of 454 pyrosequencing in 2005 was a milestone in genome sequencing in terms of performance and cost. Throughout the three available releases, average read lengths have increased to approximately 500 base pairs and are thus approaching read lengths obtained from traditional Sanger sequencing. Study design of sequencing projects would benefit from being able to simulate experiments. RESULTS: We explore 454 raw data to investigate its characteristics and derive empirical distributions for the flow values generated by pyrosequencing. Based on our findings, we implement Flowsim, a simulator that generates realistic pyrosequencing data files of arbitrary size from a given set of input DNA sequences. We finally use our simulator to examine the impact of sequence lengths on the results of concrete whole-genome assemblies, and we suggest its use in planning of sequencing projects, benchmarking of assembly methods and other fields. AVAILABILITY: Flowsim is freely available under the General Public License from http://blog.malde.org/index.php/flowsim/.
Susanne Balzer, Ketil Malde, Anders Lanzén, Animesh Sharma, Inge Jonassen
Bioinform.2
2009 Using Bloom Filters for Large Scale Gene Sequence Analysis in Haskell
Ketil Malde, Bryan O'Sullivan
PADL1
2008 The effect of sequence quality on sequence alignment
abstract
MOTIVATION: The nucleotide sequencing process produces not only the sequence of nucleotides, but also associated quality values. Quality values provide valuable information, but are primarily used only for trimming sequences and generally ignored in subsequent analyses. RESULTS: This article describes how the scoring schemes of standard alignment algorithms can be modified to take into account quality values to produce improved alignments and statistically more accurate scores. A prototype implementation is also provided, and used to post-process a set of BLAST results. Quality-adjusted alignment is a natural extension of standard alignment methods, and can be implemented with only a small constant factor performance penalty. The method can also be applied to related methods including heuristic search algorithms like BLAST and FASTA. AVAILABILITY: http://malde.org/~ketil/qaa.
Ketil Malde
Bioinform.1
2006 RBR: library-less repeat detection for ESTs
abstract
MOTIVATION: Repeat sequences in ESTs are a source of problems, in particular for clustering. ESTs are therefore commonly masked against a library of known repeats. High quality repeat libraries are available for the widely studied organisms, but for most other organisms the lack of such libraries is likely to compromise the quality of EST analysis. RESULTS: We present a fast, flexible and library-less method for masking repeats in EST sequences, based on match statistics within the EST collection. The method is not linked to a particular clustering algorithm. Extensive testing on datasets using different clustering methods and a genomic mapping as reference shows that this method gives results that are better than or as good as those obtained using RepeatMasker with a repeat library. AVAILABILITY: The implementation of RBR is available under the terms of the GPL from http://www.ii.uib.no/~ketil/bioinformatics CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Ketil Malde, Korbinian Schneeberger, Eivind Coward, Inge Jonassen
Bioinform.1
2006 Calculating PSSM probabilities with lazy dynamic programming
abstract
Position-specific scoring matrices are one way to represent approximate string patterns, which are commonly encountered in the field of bioinformatics. An important problem that arises with their application is calculating the statistical significance of matches. We review the currently most efficient algorithm for this task, and show how it can be implemented in Haskell, taking advantage of the built-in non-strictness of the language. The resulting program turns out to be an instance of dynamic programming, using lists rather the typical dynamic programming matrix.
Ketil Malde, Robert Giegerich
J. Funct. Program.1
2005 A graph based algorithm for generating EST consensus sequences
abstract
MOTIVATION: EST sequences constitute an abundant, yet error prone resource for computational biology. Expressed sequences are important in gene discovery and identification, and they are also crucial for the discovery and classification of alternative splicing. An important challenge when processing EST sequences is the reconstruction of mRNA by assembling EST clusters into consensus sequences. RESULTS: In contrast to the more established assembly tools, we propose an algorithm that constructs a graph over sequence fragments of fixed size, and produces consensus sequences as traversals of this graph. We provide a tool implementing this algorithm, and perform an experiment where the consensus sequences produced by our implementation, as well as by currently available tools, are compared to mRNA. The results show that our proposed algorithm in a majority of the cases produces consensus of higher quality than the established sequence assemblers and at a competitive speed. AVAILABILITY: The source code for the implementation is available under a GPL license from http://www.ii.uib.no/~ketil/bioinformatics/ CONTACT: [email protected].
Ketil Malde, Eivind Coward, Inge Jonassen
Bioinform.1
2003 Fast Sequence Clustering Using A Suffix Array Algorithm
abstract
MOTIVATION: Efficient clustering is important for handling the large amount of available EST sequences. Most contemporary methods are based on some kind of all-against-all comparison, resulting in a quadratic time complexity. A different approach is needed to keep up with the rapid growth of EST data. RESULTS: A new, fast EST clustering algorithm is presented. Sub-quadratic time complexity is achieved by using an algorithm based on suffix arrays. A prototype implementation has been developed and run on a benchmark data set. The produced clusterings are validated by comparing them to clusterings produced by other methods, and the results are quite promising. AVAILABILITY: The source code for the prototype implementation is available under a GPL license from http://www.ii.uib.no/~ketil/bio/.
Ketil Malde, Eivind Coward, Inge Jonassen
Bioinform.1