Abstract: The present invention enables accurate identification of organisms by analyzing their DNA sequences and, based on their DNA sequences, assessing classification annotations, such as taxonomic, systematic, or functional annotations. Sequence-based identification of life forms as described herein can be used for diagnostic purposes, for example. Further, the techniques disclosed herein offer advantages over conventional culture-based techniques. Example embodiments are related to methods for assessing classification annotations assigned to DNA sequences of organisms. One example embodiment includes a method of identifying a centroid DNA sequence of one or more organisms. The method includes obtaining a plurality of DNA sequences from one or more organisms, annotating each DNA sequence with a classification annotation, and grouping the plurality of DNA sequences into a plurality of groups.

Abstract: For assessing classification annotations assigned to DNA sequences stored in a reference database, the DNA sequences are grouped by species (S1) using established classification schemes. Subsequently, a measure of distance between pairs of DNA sequences is determined (S41) by aligning (S31) the respective sequences and determining the measure of distance (S41) based on a score of similarity between the aligned DNA sequences. Determined are one or more centroid sequences (S42) which have the shortest aggregate measure of distance to the other DNA sequences in the respective group (species). Assigned to the DNA sequences (S5) as a quantitative confidence level for their classification annotations is in each case the measure of distance between the respective DNA sequence and the centroid sequence.

Abstract: To identify organism types from a target gene sequence, a server receives (S1) a target reference from a user via a telecommunications network. From a plurality of type-specific profiles, defining informative sequence regions for differentiating individual organisms, selected (S2) automatically is a profile having a highest correlation with the target gene sequence. The target gene sequence is compared (S4) automatically to reference sequences related to the selected profile. The comparison results related to the informative sequence regions are weighted (S5) and, from the reference sequences, determined (S9) is the organism type associated with the type-specific reference sequence, having a best match with the target gene sequence. The best match is determined based on the weighted comparison results. The profile search and weighted alignment provides identification of organism types from a target gene sequence while discriminating between trivial and significant inter-sequence differences.

Abstract: To validate DNA sequencing data from sequence data of one or more DNA fragments, a server (3) obtains a target specification from a user via a telecommunications network (2). From a set of one or more possible reference sequences (42), related to the target specification and stored in a database (4), the server (3) selects the reference sequence having the highest correlation with the fragment sequence data. For example, if the target specification identifies a gene sequence, then the reference sequence is selected from a set of variants of the gene sequence. Automatically, the server (3) aligns the fragment sequence data with the selected reference sequence and identifies any sequence positions where nucleotide codes of aligned fragment sequence data and selected reference sequence do not correspond.

Abstract: The invention relates to oligonucleotides for the qualitative and/or quantitative amplification and/or the sequencing of 16S rDNA-genes, as well as of fragments thereof and RNA derived thereof. It relates to their use as primers in amplification reactions and in sequencing, in particular in combination for the identification of the genus/species/strain of the bacterial sample or clinical isolate.

Abstract: For assessing classification annotations assigned to DNA sequences stored in a reference database, the DNA sequences are grouped by species using established classification schemes. Subsequently, a measure of distance between pairs of DNA sequences is determined by aligning the respective sequences and determining the measure of distance based on a score of similarity between the aligned DNA sequences. Determined are one or more centroid sequences which have the shortest aggregate measure of distance to the other DNA sequences in the respective group (species). Assigned to the DNA sequences as a quantitative confidence level for their classification annotations is in each case the measure of distance between the respective DNA sequence and the centroid sequence. The assessment and rating of the classification annotations with these confidence levels make it possible to provide to a user a quantitative indication of the degree of representativeness of a DNA sequence for a particular species.

Abstract: To identify organism types from a target gene sequence, a server receives (S1) a target reference from a user via a telecommunications network. From a plurality of type-specific profiles, defining informative sequence regions for differentiating individual organisms, selected (S2) automatically is a profile having a highest correlation with the target gene sequence. The target gene sequence is compared (S4) automatically to reference sequences related to the selected profile. The comparison results related to the informative sequence regions are weighted (S5) and, from the reference sequences, determined (S9) is the organism type associated with the type-specific reference sequence, having a best match with the target gene sequence. The best match is determined based on the weighted comparison results. The profile search and weighted alignment provides identification of organism types from a target gene sequence while discriminating between trivial and significant inter-sequence differences.

Abstract: To validate DNA sequencing data from sequence data of one or more DNA fragments, a server (3) obtains a target specification from a user via a telecommunications network (2). From a set of one or more possible reference sequences (42), related to the target specification and stored in a database (4), the server (3) selects the reference sequence having the highest correlation with the fragment sequence data. For example, if the target specification identifies a gene sequence, then the reference sequence is selected from a set of variants of the gene sequence. Automatically, the server (3) aligns the fragment sequence data with the selected reference sequence and identifies any sequence positions where nucleotide codes of aligned fragment sequence data and selected reference sequence do not correspond.