JAX Colony Management System (JCMS): an extensible colony and phenotype data management system

The Jackson Laboratory Colony Management System (JCMS) is a software application for managing data and information related to research mouse colonies, associated biospecimens, and experimental protocols. JCMS runs directly on computers that run one of the PC Windows^® operating systems, but can be accessed via web browser interfaces from any computer running a Windows, Macintosh^®, or Linux^® operating system. JCMS can be configured for a single user or multiple users in small- to medium-size work groups. The target audience for JCMS includes laboratory technicians, animal colony managers, and principal investigators. The application provides operational support for colony management and experimental workflows, sample and data tracking through transaction-based data entry forms, and date-driven work reports. Flexible query forms allow researchers to retrieve database records based on user-defined criteria. Recent advances in handheld computers with integrated barcode readers, middleware technologies, web browsers, and wireless networks add to the utility of JCMS by allowing real-time access to the database from any networked computer.     

GARBAN II: an integrative framework for extracting biological information from proteomic and genomic data

Genomic and proteomic analyses generate a massive amount of data that requires specific bioinformatic tools for its management and interpretation. GARBAN II, developed from the previous GARBAN platform, provides an integrated framework to simultaneously analyse and compare multiple datasets from DNA microarrays and proteomic studies. The general architecture, gene classification and comparison, and graphical representation have been redesigned to ensure a user-friendly feature and to improve the capabilities and efficiency of this system. Additionally, GARBAN II has been extended with new applications to display networks of coexpressed genes and to integrate access to BioRag and MotifScanner so as to facilitate the holistic analysis of users' data.     

The PACRAT system: an extensible WWW-based system for correlated sequence retrieval, storage and analysis

With PACRAT (Patterns, Analyses, Correlations. Remote Archive Testbed) we present an online database solution to the problem of accessing high-confidence sequences with specific relationships to classes of genes, such as upstream intergenic regions attached to tRNA genes. In addition the software contains a data warehousing and analysis-facilitating suite to streamline the process of analyzing the collected data. An unexpected additional benefit of the system is that it also provides easy access to sequences of lower confidence, and may be of assistance in such things as resolving ORF-call conflicts in genomic annotation projects.     

PheMaDB: A solution for storage,retrieval, and analysis of high throughput phenotype data

Background  

OmniLog™ phenotype microarrays (PMs) have the capability to measure and compare the growth responses of biological samples upon exposure to hundreds of growth conditions such as different metabolites and antibiotics over a time course of hours to days. In order to manage the large amount of data produced from the OmniLog™ instrument, PheMaDB (Phenotype Microarray DataBase), a web-based relational database, was designed. PheMaDB enables efficient storage, retrieval and rapid analysis of the OmniLog™ PM data.     

Sterile host yeasts (SHY): a eukaryotic system of biological containment for recombinant DNA experiments.

A system of biological containment for recombinant DNA experiments in Saccharomyces cerevisiae (Brewer's/Baker's yeast) is described. The principle of containment is sterility: the haploid host strains all contain a mating-type-non-specific sterile mutation. The hosts also contain four auxotrophic mutations suitable for selection for the various kinds of vectors used. All vectors are derivatives of pBR322 which can be selected and maintained in both yeast and Escherichia coli. The system has recently been certified at the HV2 level by the National Institutes of Health.     

BIOZON: a system for unification, management and analysis of heterogeneous biological data

Background  

Integration of heterogeneous data types is a challenging problem, especially in biology, where the number of databases and data types increase rapidly. Amongst the problems that one has to face are integrity, consistency, redundancy, connectivity, expressiveness and updatability.     

SpaCEM3: a software for biological module detection when data is incomplete, high dimensional and dependent

SUMMARY: Among classical methods for module detection, SpaCEM(3) provides ad hoc algorithms that were shown to be particularly well adapted to specific features of biological data: high-dimensionality, interactions between components (genes) and integrated treatment of missingness in observations. The software, currently in its version 2.0, is developed in C++ and can be used either via command line or with the GUI under Linux and Windows environments. AVAILABILITY: The SpaCEM(3) software, a documentation and datasets are available from http://spacem3.gforge.inria.fr/.     

Clustering Deviation Index (CDI): a robust and accurate internal measure for evaluating scRNA-seq data clustering

Single-cell high-throughput chromatin conformation capture methodologies (scHi-C) enable profiling of long-range genomic interactions. However, data from these technologies are prone to technical noise and biases that hinder downstream analysis. We develop a normalization approach, BandNorm, and a deep generative modeling framework, scVI-3D, to account for scHi-C specific biases. In benchmarking experiments, BandNorm yields leading performances in a time and memory efficient manner for cell-type separation, identification of interacting loci, and recovery of cell-type relationships, while scVI-3D exhibits advantages for rare cell types and under high sparsity scenarios. Application of BandNorm coupled with gene-associating domain analysis reveals scRNA-seq validated sub-cell type identification.     

The protein information and property explorer: an easy-to-use, rich-client web application for the management and functional analysis of proteomic data

MOTIVATION: Mass spectrometry experiments in the field of proteomics produce lists containing tens to thousands of identified proteins. With the protein information and property explorer (PIPE), the biologist can acquire functional annotations for these proteins and explore the enrichment of the list, or fraction thereof, with respect to functional classes. These protein lists may be saved for access at a later time or different location. The PIPE is interoperable with the Firegoose and the Gaggle, permitting wide-ranging data exploration and analysis. The PIPE is a rich-client web application which uses AJAX capabilities provided by the Google Web Toolkit, and server-side data storage using Hibernate. AVAILABILITY: http://pipe.systemsbiology.net.     

Single Molecule Analysis Research Tool (SMART): an integrated approach for analyzing single molecule data

Single molecule studies have expanded rapidly over the past decade and have the ability to provide an unprecedented level of understanding of biological systems. A common challenge upon introduction of novel, data-rich approaches is the management, processing, and analysis of the complex data sets that are generated. We provide a standardized approach for analyzing these data in the freely available software package SMART: Single Molecule Analysis Research Tool. SMART provides a format for organizing and easily accessing single molecule data, a general hidden Markov modeling algorithm for fitting an array of possible models specified by the user, a standardized data structure and graphical user interfaces to streamline the analysis and visualization of data. This approach guides experimental design, facilitating acquisition of the maximal information from single molecule experiments. SMART also provides a standardized format to allow dissemination of single molecule data and transparency in the analysis of reported data.     

Multiple data sets, high homoplasy, and the phylogeny of softshell turtles (Testudines: Trionychidae)

We present a phylogenetic hypothesis and novel, rank-free classification for all extant species of softshell turtles (Testudines:Trionychidae). Our data set included DNA sequence data from two mitochondrial protein-coding genes and a approximately 1-kb nuclear intron for 23 of 26 recognized species, and 59 previously published morphological characters for a complimentary set of 24 species. The combined data set provided complete taxonomic coverage for this globally distributed clade of turtles, with incomplete data for a few taxa. Although our taxonomic sampling is complete, most of the modern taxa are representatives of old and very divergent lineages. Thus, due to biological realities, our sampling consists of one or a few representatives of several ancient lineages across a relatively deep phylogenetic tree. Our analyses of the combined data set converge on a set of well-supported relationships, which is in accord with many aspects of traditional softshell systematics including the monophyly of the Cyclanorbinae and Trionychinae. However, our results conflict with other aspects of current taxonomy and indicate that most of the currently recognized tribes are not monophyletic. We use this strong estimate of the phylogeny of softshell turtles for two purposes: (1) as the basis for a novel rank-free classification, and (2) to retrospectively examine strategies for analyzing highly homoplasious mtDNA data in deep phylogenetic problems where increased taxon sampling is not an option. Weeded and weighted parsimony, and model-based techniques, generally improved the phylogenetic performance of highly homoplasious mtDNA sequences, but no single strategy completely mitigated the problems of associated with these highly homoplasious data. Many deep nodes in the softshell turtle phylogeny were confidently recovered only after the addition of largely nonhomoplasious data from the nuclear intron.     

Microarray Data Analysis Toolbox (MDAT): for normalization, adjustment and analysis of gene expression data

SUMMARY: We introduce a novel Matlab toolbox for microarray data analysis. This toolbox uses normalization based upon a normally distributed background and differential gene expression based on five statistical measures. The objects in this toolbox are open source and can be implemented to suit your application. AVAILABILITY: MDAT v1.0 is a Matlab toolbox and requires Matlab to run. MDAT is freely available at http://microarray.omrf.org/publications/2004/knowlton/MDAT.zip.     

The [Ru(Hedta)NO](0.1-) system: structure, chemical reactivity and biological assays

The [Ru(II)(Hedta)NO(+)] complex is a diamagnetic species crystallizing in a distorted octahedral geometry, with the Ru-N(O) length 1.756(4) A and the RuNO angle 172.3(4) degrees . The complex contains one protonated carboxylate (pK(a)=2.7+/-0.1). The [Ru(II)(Hedta)NO(+)] complex undergoes a nitrosyl-centered one-electron reduction (chemical or electrochemical), with E(NO+/NO)=-0.31 V vs SCE (I=0.2 M, pH 1), yielding [Ru(II)(Hedta)NO](-), which aquates slowly: k(-NO)=2.1+/-0.4x10(-3) s(-1) (pH 1.0, I=0.2 M, CF(3)COOH/NaCF(3)COO, 25 degrees C). At pHs>12, the predominant species, [Ru(II)(edta)NO](-), reacts according to [Ru(II)(edta)NO](-)+2OH(-)-->[Ru(II)(edta)NO(2)](3-), with K(eq)=1.0+/-0.4 x 10(3) M(-2) (I=1.0 M, NaCl; T=25.0+/-0.1 degrees C). The rate-law is first order in each of the reactants for most reaction conditions, with k(OH(-))=4.35+/-0.02 M(-1)s(-1) (25.0 degrees C), assignable mechanistically to the elementary step comprising the attack of one OH(-) on [Ru(II)(edta)NO](-), with subsequent fast deprotonation of the [Ru(II)(edta)NO(2)H](2-) intermediate. The activation parameters were DeltaH(#)=60+/-1 kJ/mol, DeltaS(#)=-31+/-3 J/Kmol, consistent with a nucleophilic addition process between likely charged ions. In the toxicity up-and-down tests performed with Swiss mice, no death was observed in all the doses administered (3-9.08 x 10(-5) mol/kg). The biodistribution tests performed with Wistar male rats showed metal in the liver, kidney, urine and plasma. Eight hours after the injection no metal was detected in the samples. The vasodilator effect of [Ru(II)(edta)NO](-) was studied in aortic rings without endothelium, and was compared with sodium nitroprusside (SNP). The times of maximal effects of [Ru(II)(edta)NO](-) and SNP were 2 h and 12 min, respectively, suggesting that [Ru(II)(edta)NO](-) releases NO slowly to the medium in comparison with SNP.     

Redberry mite, Acalitus essigi (Hassan) (Acari: Eriophyidae), an additional biological control agent for Rubus species (blackberry) (Rosaceae) in Australia

Abstract  Acalitus essigi , the eriophyoid mite that causes red berry disease in Rubus species (Rosaceae), was collected from the fruits of three species of weedy blackberry, R. anglocandicans , R. laudatus and R. ulmifolius , in south-west Australia. This is the first record for this species in Western Australia and these plants appear to be new host records for A. essigi , which causes uneven ripening of fruit. Information on the mite is reviewed in the context of determining its potential as a biological control agent for Rubus species, especially those that are not susceptible to Phragmidium violaceum (Uredinales), the rust fungus being released against species of European blackberry in Australia. Published records also show that A. essigi will attack a wide range of Rubus species including species of North American origin that currently escape biological control in Australia. It may also be useful for preventing the spread of commercial varieties of Rubus (e.g. raspberry and loganberry) that have escaped to become weedy. However, the mite may have limited dispersal ability and thus require redistribution.     

Selected Research Articles from the 2019 International Workshop on Computational Network Biology: Modeling,Analysis, and Control (CNB-MAC)

Background

Haplotypes, the ordered lists of single nucleotide variations that distinguish chromosomal sequences from their homologous pairs, may reveal an individual’s susceptibility to hereditary and complex diseases and affect how our bodies respond to therapeutic drugs. Reconstructing haplotypes of an individual from short sequencing reads is an NP-hard problem that becomes even more challenging in the case of polyploids. While increasing lengths of sequencing reads and insert sizes helps improve accuracy of reconstruction, it also exacerbates computational complexity of the haplotype assembly task. This has motivated the pursuit of algorithmic frameworks capable of accurate yet efficient assembly of haplotypes from high-throughput sequencing data.

Results

We propose a novel graphical representation of sequencing reads and pose the haplotype assembly problem as an instance of community detection on a spatial random graph. To this end, we construct a graph where each read is a node with an unknown community label associating the read with the haplotype it samples. Haplotype reconstruction can then be thought of as a two-step procedure: first, one recovers the community labels on the nodes (i.e., the reads), and then uses the estimated labels to assemble the haplotypes. Based on this observation, we propose ComHapDet – a novel assembly algorithm for diploid and ployploid haplotypes which allows both bialleleic and multi-allelic variants.

Conclusions

Performance of the proposed algorithm is benchmarked on simulated as well as experimental data obtained by sequencing Chromosome 5 of tetraploid biallelic Solanum-Tuberosum (Potato). The results demonstrate the efficacy of the proposed method and that it compares favorably with the existing techniques.

     

Denitrification and anammox in tropical aquaculture settlement ponds: an isotope tracer approach for evaluating n(2) production

Settlement ponds are used to treat aquaculture discharge water by removing nutrients through physical (settling) and biological (microbial transformation) processes. Nutrient removal through settling has been quantified, however, the occurrence of, and potential for microbial nitrogen (N) removal is largely unknown in these systems. Therefore, isotope tracer techniques were used to measure potential rates of denitrification and anaerobic ammonium oxidation (anammox) in the sediment of settlement ponds in tropical aquaculture systems. Dinitrogen gas (N₂) was produced in all ponds, although potential rates were low (0–7.07 nmol N cm⁻³ h⁻¹) relative to other aquatic systems. Denitrification was the main driver of N₂ production, with anammox only detected in two of the four ponds. No correlations were detected between the measured sediment variables (total organic carbon, total nitrogen, iron, manganese, sulphur and phosphorous) and denitrification or anammox. Furthermore, denitrification was not carbon limited as the addition of particulate organic matter (paired t-Test; P = 0.350, n = 3) or methanol (paired t-Test; P = 0.744, n = 3) did not stimulate production of N₂. A simple mass balance model showed that only 2.5% of added fixed N was removed in the studied settlement ponds through the denitrification and anammox processes. It is recommended that settlement ponds be used in conjunction with additional technologies (i.e. constructed wetlands or biological reactors) to enhance N₂ production and N removal from aquaculture wastewater.