Pfp-fm: an accelerated FM-index.

FM-indexes are crucial data structures in DNA alignment, but searching with them usually takes at least one random access per character in the query pattern. Ferragina and Fischer [1] observed in 2007 that word-based indexes often use fewer random accesses than character-based indexes, and thus support faster searches. Since DNA lacks natural word-boundaries, however, it is necessary to parse it somehow before applying word-based FM-indexing.

PFP-FM: An Accelerated FM-index.

FM-indexes are a crucial data structure in DNA alignment, but searching with them usually takes at least one random access per character in the query pattern. Ferragina and Fischer [1] observed in 2007 that word-based indexes often use fewer random accesses than character-based indexes, and thus support faster searches. Since DNA lacks natural word-boundaries, however, it is necessary to parse it somehow before applying word-based FM-indexing.

The current status of emergency departments in secondary emergency medical institutions in Japan: a questionnaire survey.

Background: While emergency medicine (ER)-based emergency care is prevalent in many countries, in Japan, the "department-specific emergency care model" and the "emergency center model" are mainstream. We hypothesized that many secondary emergency medical institutions in Japan have inadequate systems. Using a questionnaire, we investigated the status of and problems in the emergency medical services system in secondary emergency medical institutions in Japan.

HaploBlocks: Efficient Detection of Positive Selection in Large Population Genomic Datasets.

Genomic regions under positive selection harbor variation linked for example to adaptation. Most tools for detecting positively selected variants have computational resource requirements rendering them impractical on population genomic datasets with hundreds of thousands of individuals or more. We have developed and implemented an efficient haplotype-based approach able to scan large datasets and accurately detect positive selection.

Finding all maximal perfect haplotype blocks in linear time.

Recent large-scale community sequencing efforts allow at an unprecedented level of detail the identification of genomic regions that show signatures of natural selection. Traditional methods for identifying such regions from individuals' haplotype data, however, require excessive computing times and therefore are not applicable to current datasets. In 2019, Cunha et al.

Transcriptional profiling of hematopoietic stem cells by high-throughput sequencing.

Microarray analysis has made it feasible to carry out extensive gene expression profiling in a single assay. Various hematopoietic stem cell (HSC) populations have been subjected to microarray analyses and their profiles of gene expression have been reported. However, this approach is not suitable to identify novel transcripts or for profiling of genes with low expression levels.

An O(N2) algorithm for discovering optimal Boolean pattern pairs.

We consider the problem of finding the optimal combination of string patterns, which characterizes a given set of strings that have a numeric attribute value assigned to each string. Pattern combinations are scored based on the correlation between their occurrences in the strings and the numeric attribute values. The aim is to find the combination of patterns which is best with respect to an appropriate scoring function.

Contribution of comparative fish studies to general endocrinology: structure and function of some osmoregulatory hormones.

Fish endocrinologists are commonly motivated to pursue their research driven by their own interests in these aquatic animals. However, the data obtained in fish studies not only satisfy their own interests but often contribute more generally to the studies of other vertebrates, including mammals. The life of fishes is characterized by the aquatic habitat, which demands many physiological adjustments distinct from the terrestrial life.

Utilizing evolutionary information and gene expression data for estimating gene networks with bayesian network models.

Since microarray gene expression data do not contain sufficient information for estimating accurate gene networks, other biological information has been considered to improve the estimated networks. Recent studies have revealed that highly conserved proteins that exhibit similar expression patterns in different organisms, have almost the same function in each organism. Such conserved proteins are also known to play similar roles in terms of the regulation of genes.

Efficiently finding regulatory elements using correlation with gene expression.

We present an efficient algorithm for detecting putative regulatory elements in the upstream DNA sequences of genes, using gene expression information obtained from microarray experiments. Based on a generalized suffix tree, our algorithm looks for motif patterns whose appearance in the upstream region is most correlated with the expression levels of the genes. We are able to find the optimal pattern, in time linear in the total length of the upstream sequences.

Identification of novel adrenomedullin in mammals: a potent cardiovascular and renal regulator.

We have identified cDNA encoding a new member of the adrenomedullin (AM) family, AM2, for the first time in mammals (mouse, rat and human). The predicted precursor carried mature AM2 in the C-terminus, which had an intramolecular ring formed by an S-S bond and a possibly amidated C-terminus. Phylogenetic analyses clustered AM2 and AM into two distinct but closely related groups.

A string pattern regression algorithm and its application to pattern discovery in long introns.

We present a new approach to pattern discovery called string pattern regression, where we are given a data set that consists of a string attribute and an objective numerical attribute. The problem is to find the best string pattern that divides the data set in such a way that the distribution of the numerical attribute values of the set for which the pattern matches the string attribute, is most distinct, with respect to some appropriate measure, from the distribution of the numerical attribute values of the set for which the pattern does not match the string attribute. By solving this problem, we are able to discover, at the same time, a subset of the data whose objective numerical attributes are significantly different from rest of the data, as well as the splitting rule in the form of a string pattern that is conserved in the subset.

Estimating gene networks from gene expression data by combining Bayesian network model with promoter element detection.

We present a statistical method for estimating gene networks and detecting promoter elements simultaneously. When estimating a network from gene expression data alone, a common problem is that the number of microarrays is limited compared to the number of variables in the network model, making accurate estimation a difficult task. Our method overcomes this problem by integrating the microarray gene expression data and the DNA sequence information into a Bayesian network model.

Extensive feature detection of N-terminal protein sorting signals.

Motivation: The prediction of localization sites of various proteins is an important and challenging problem in the field of molecular biology. TargetP, by Emanuelsson et al. (J.