MotivationThe elucidation of all inter protein interactions would significantly enhance our knowledge of cellular processes at a molecular level. Given the enormity of the problem, the expenses and limitations of experimental methods, it is imperative that this problem is tackled computationally. In silico predictions of protein interactions entail sampling different conformations of the purported

MotivationComputing the uniqueness of k-mers for each position of a genome while allowing for up to e mismatches is computationally challenging. However, it is crucial for many biological applications such as the design of guide RNA for CRISPR experiments. More formally, the uniqueness or (k, e)-mappability can be described for every position as the reciprocal value of how often this k-mer occurs approximately

MotivationSingle-cell RNA-sequencing (scRNA-Seq) profiles transcriptome of individual cells, which enables the discovery of cell types or subtypes by using unsupervised clustering. Current algorithms perform dimension reduction before cell clustering because of noises, high dimensionality, and linear inseparability of scRNA-seq data. However, independence of dimension reduction and clustering fails

MotivationLarge scale genome-wide association studies (GWAS) have resulted in the identification of a wide range of genetic variants related to a host of complex traits and disorders. Despite their success, the individual-SNP analysis approach adopted in most current GWAS can be limited in that it is usually biologically simple to elucidate a comprehensive genetic architecture of phenotypes and statistically

MotivationProgrammed DNA elimination plays a crucial role in the transitions between germline and somatic genomes in diverse organisms ranging from unicellular ciliates to multicellular nematodes. However, software specific to the detection of DNA splicing events is scarce. In this paper, we describe ADFinder, an efficient detector of programmed DNA eliminations using NGS high-throughput sequencing

MotivationIdentifying the genes regulated by a given transcription factor (its “target genes”) is a key step in developing a comprehensive understanding of gene regulation. Previously we developed a method (CisMapper) for predicting the target genes of a transcription factor (TF) based solely on the correlation between a histone modification at the TF’s binding site and the expression of the gene across

MotivationIdentification of virulence factors (VFs) is critical to the elucidation of bacterial pathogenesis and prevention of related infectious diseases. Current computational methods for VF prediction focus on binary classification or involve only several class(es) of VFs with sufficient samples. However, thousands of VF classes are present in real-world scenarios, and many of them only have a very

Summary Fully realizing the promise of personalized medicine will require rapid and accurate classification of pathogenic human variation. Multiplexed assays of variant effect (MAVEs) can experimentally test nearly all possible missense variants in selected gene targets. Planning a MAVE study involves identifying target genes with clinical impact, and identifying scalable functional assays for that

SummaryTranscription and DNA supercoiling are involved in a complex, dynamical and nonlinear coupling that results from the basal interaction between DNA and RNA Polymerase. We present the first software to simulate this coupling, applicable to a wide range of bacterial organisms. TwisTranscripT allows quantifying its contribution in global transcriptional regulation, and provides a mechanistic basis

MotivationDeveloping methods to efficiently analyze 3D point cloud data of plant architectures remains challenging for many phenotyping applications. Here, we describe a tool that tackles four core phenotyping tasks: classification of cloud points into stem and lamina points; graph skeletonization of the stem points; segmentation of individual lamina; and whole leaf labeling. These four tasks are critical

MotivationGene Network Inference and Master Regulator Analysis (MRA) have been widely adopted to define specific transcriptional perturbations from gene expression signatures. Several tools exist to perform such analyses, but most require a computer cluster or large amounts of RAM to be executed. ResultsWe developed corto, a fast and lightweight R package to infer gene networks and perform MRA from

MotivationSince December 2019, the newly identified coronavirus SARS-CoV-2 has caused a massive health crisis worldwide and resulted in over 70,000 COVID-19 infections so far. Clinical drugs targeting SARS-CoV-2 are urgently needed to decrease the high fatality rate of confirmed COVID-19 patients. Traditional de novo drug discovery needs more than 10 years, so drug repurposing seems the best option

SummaryScaffoldGraph (SG) is an open-source Python library and command-line tool for the generation and analysis of molecular scaffold networks and trees, with the capability of processing large sets of input molecules. With the increase in high-throughput screening (HTS) data, scaffold graphs have proven useful for the navigation and analysis of chemical space, being used for visualisation, clustering

MotivationProtein domains are subunits that can fold and function independently. Correct domain boundary assignment is thus a critical step towards accurate protein structure and function analyses. There is, however, no efficient algorithm available for accurate domain prediction from sequence. The problem is particularly challenging for proteins with discontinuous domains, which consist of domain

MotivationThe submission of annotated sequence data to public sequence databases constitutes a central pillar in biological research. The surge of novel DNA sequences awaiting database submission due to the application of next-generation sequencing has increased the need for software tools that facilitate bulk submissions. This need has yet to be met with the concurrent development of tools to automate

MotivationRecently, multi-objective swarm intelligence optimization (SIO) algorithms have attracted considerable attention as disease model-free methods for detecting high-order single nucleotide polymorphism (SNP) interactions. However, a strict Pareto optimal set may filter out some of the SNP combinations associated with disease status. Furthermore, the lack of heuristic factors for finding SNP

MotivationEpistasis reflects the distortion on a particular trait or phenotype resulting from the combinatorial effect of two or more genes or genetic variants. Epistasis is an important genetic foundation underlying quantitative traits in many organisms as well as in complex human diseases. However, there are two major barriers in identifying epistasis using large genomic data sets. One is that epistasis

MotivationSynthetic lethality (SL) is a promising form of gene interaction for cancer therapy, as it is able to identify specific genes to target at cancer cells without disrupting normal cells. As high-throughput wet-lab settings are often costly and face various challenges, computational approaches have become a practical complement. In particular, predicting SLs can be formulated as a link prediction

SummaryWe have developed a software tool to improve the image quality in FIB-SEM stacks: PolishEM. Based on a Gaussian-blur model, it automatically estimates and compensates for the blur affecting each individual image. It also includes correction for artefacts commonly arising in FIB-SEM (e.g. curtaining). PolishEM has been optimized for an efficient processing of huge FIB-SEM stacks on standard computers

MotivationComparing the organization of gene, gene clusters, and their flanking genomic contexts is of critical importance to the determination of gene function and evolutionary basis of microbial traits. Currently, user-friendly and flexible tools enabling to visualize and compare genomic contexts for numerous genomes are still missing. ResultsWe here present Gcluster, a stand-alone Perl tool that

SummaryQuartataWeb is a user-friendly server developed for polypharmacological and chemogenomics analyses. Users can easily obtain information on experimentally verified (known) and computationally predicted (new) interactions between 5,494 drugs and 2,807 human proteins in DrugBank, and between 315,514 chemicals and 9,457 human proteins in the STITCH database. In addition, QuartataWeb links targets

MotivationTNT (a widely used program for phylogenetic analysis) includes an interpreter for a scripting language, but that implementation is non-standard and uses several conventions of its own. This paper describes the implementation and basic usage of a C-interpreter (with all the ISO essentials) now included in TNT. A phylogenetic library includes functions that can be used for manipulating trees

MotivationWhole genome sequencing (WGS) is widely used for copy number variation (CNV) detection. However, for most bacteria, their circular genome structure and high replication rate make reads more enriched near the replication origin. CNV detection based on read depth could be seriously influenced by such replication bias. ResultsWe show that the replication bias is widespread using ~200 bacterial

SummaryWe develop a fully unsupervised deconvolution method to dissect complex tissues into molecularly distinctive tissue or cell subtypes based on bulk expression profiles. We implement an R package, deconvolution by Convex Analysis of Mixtures (debCAM) that can automatically detect tissue/cell-specific markers, determine the number of constituent sub-types, calculate subtype proportions in individual

MotivationHigh-throughput sequencing discovers many naturally occurring disulfide-rich peptides or cystine-rich peptides (CRPs) with diversified bioactivities. However, their structure information, which is very important to peptide drug discovery, is still very limited. ResultsWe have developed a CRP-specific structure prediction method called CRiSP, based on a customized template database with cystine-specific

MotivationThe rapid proliferation of single-cell RNA-Sequencing (scRNA-Seq) technologies has spurred the development of diverse computational approaches to detect transcriptionally coherent populations. While the complexity of the algorithms for detecting heterogeneity has increased, most require significant user-tuning, are heavily reliant on dimension reduction techniques and are not scalable to

Dimensionality reduction is a key step in the analysis of single-cell RNA sequencing data. It produces a low-dimensional embedding for visualization and as a calculation base for downstream analysis. Nonlinear techniques are most suitable to handle the intrinsic complexity of large, heterogeneous single cell data. However, with no linear relation between gene and embedding coordinate, there is no way

MotivationThe discrimination ability of score functions to separate correct from incorrect peptide-spectrum matches in database-searching-based spectrum identification are hindered by many superfluous peaks belonging to unexpected fragmentation ions or by the lacking peaks of anticipated fragmentation ions. ResultsHere, we present a new method, called BoltzMatch, to learn score functions using a particular

MotivationProtein Structural Annotations are essential abstractions to deal with the prediction of Protein Structures. Many increasingly sophisticated Protein Structural Annotations have been devised in the last few decades. However the need for annotations that are easy to compute, process and predict has not diminished. This is especially true for protein structures that are hardest to predict such

MotivationBiological pathway is important curated knowledge of biological processes. Thus, cancer subtype classification based on pathways will be very useful to understand differences in biological mechanisms among cancer subtypes. However, pathways include only a fraction of the entire gene set, only 1/3 of human genes in KEGG, and pathways are fragmented. For this reason, there are few computational

MotivationHiChIP is a powerful tool to interrogate 3D chromatin organization. Current tools to analyse chromatin looping mechanisms using HiChIP data require the identification of loop anchors to work properly. However, current approaches to discover these anchors from HiChIP data are not satisfactory, having either a very high false discovery rate or strong dependence on sequencing depth. Moreover

MotivationPopulation stratification (PS) is a major confounder in genome-wide association studies (GWAS) and can lead to false positive associations. To adjust for PS, principal component analysis (PCA)-based ancestry prediction has been widely used. Simple projection (SP) based on principal component loadings and the recently developed data augmentation-decomposition-transformation (ADP), such as

Bioinformatics (2019) doi:10.1093/bioinformatics/btz663

MotivationT-cell receptors (TCRs) are immune proteins that primarily target peptide antigens presented by the major histocompatibility complex. They tend to have lower specificity and affinity than their antibody counterparts, and their binding sites have been shown to adopt multiple conformations, which is potentially an important factor for their polyspecificity. None of the current TCR modelling

SummarySequence logos were introduced nearly 30 years ago as a human-readable format for representing consensus sequences, and they remain widely used. As new experimental and computational techniques have developed, logos have been extended: extra symbols represent covalent modifications to nucleotides, logos with multiple letters at each position illustrate models with multi-nucleotide features,

MotivationLiquid chromatography–mass spectrometry-based non-targeted metabolomics is routinely performed to qualitatively and quantitatively analyze a tremendous amount of metabolite signals in complex biological samples. However, false-positive peaks in the datasets are commonly detected as metabolite signals by using many popular software, resulting in non-reliable measurement. ResultsTo reduce false-positive

SummaryPower analysis is essential to decide the sample size of metagenomic sequencing experiments in a case-control study for identifying differentially abundant microbes. However, the complexity of microbial data characteristics such as excessive zeros, over-dispersion, compositionality, intrinsically microbial correlations and variable sequencing depths makes the power analysis particularly challenging

MotivationBisulfite sequencing (BS-seq) is a state-of-the-art technique for investigating methylation of the DNA to gain insights into the epigenetic regulation. Several algorithms have been published for identification of differentially methylated regions (DMRs). However, the performances of the individual methods remain unclear and it is difficult to optimally select an algorithm in application settings

MotivationThe Protein Data Bank (PDB), the ultimate source for data in structural biology, is inherently imbalanced. To alleviate biases, virtually all structural biology studies use non-redundant subsets of the PDB, which include only a fraction of the available data. An alternative approach, dubbed redundancy-weighting, down-weights redundant entries rather than discarding them. This approach may

MotivationImproved DNA technology has made it practical to estimate single nucleotide polymorphism (SNP)-heritability among distantly related individuals with unknown relationships. For growth and development related traits, it is meaningful to base SNP-heritability estimation on longitudinal data due to the time-dependency of the process. However, only few statistical methods have been developed so

MotivationMotivation: It is a fundamental task to identify microRNAs (miRNA) targets and accurately locate their target sites. Genome-scale experiments for miRNA target site detection are still costly. The prediction accuracies of existing computational algorithms and tools are often not up to the expectation due to a large number of false positives. One major obstacle to achieve a higher accuracy

MotivationClassification of archaeological animal samples is commonly achieved via manual examination of MALDI-ToF spectra. This is a time-consuming process which requires significant training and which does not produce a measure of confidence in the classification. We present a new, automated method for arriving at a classification of a MALDI-ToF sample, provided the collagen sequences for each candidate

MotivationGlycan structures are commonly represented using symbols or linear nomenclature such as that from the Consortium for Functional Glycomics (CFG) (also known as modified IUPAC condensed nomenclature). No current tool allows for writing the name in such format using a graphical user interface (GUI); thus, names are prone to errors or non-standardized representations. ResultsHere we present GlycoGlyph

MotivationSingle-cell RNA-seq makes possible the investigation of variability in gene expression among cells, and dependence of variation on cell type. Statistical inference methods for such analyses must be scalable, and ideally interpretable ResultsWe present an approach based on a modification of a recently published highly scalable variational autoencoder framework that provides interpretability

MotivationStatistical analyses of high-throughput sequencing data have re-shaped the biological sciences. In spite of myriad advances, recovering interpretable biological signal from data corrupted by technical noise remains a prevalent open problem. Several classes of procedures, among them classical dimensionality reduction techniques and others incorporating subject-matter knowledge, have provided

MotivationHigh-throughput protein screening is a critical technique for dissecting and designing protein function. Libraries for these assays can be created through a number of means, including targeted or random mutagenesis of a template protein sequence or direct DNA synthesis. However, mutagenic library construction methods often yield vastly more non-functional than functional variants and, despite

MotivationLow-dimensional representations of high-dimensional data are routinely employed in biomedical research to visualize, interpret and communicate results from different pipelines. In this article, we propose a novel procedure to directly estimate t-SNE embeddings that are not driven by batch effects. Without correction, interesting structure in the data can be obscured by batch effects. The

MotivationMicrobiome-metabolome association studies have experienced exponential growth for an in-depth understanding of the impact of microbiota on human health over the last decade. However, analyzing the resulting multi-omics data and their correlations remains a significant challenge due to the lack of a comprehensive computational tool that can facilitate data integration and interpretation. In

SummarySearching for homology in the vast amount of sequence data has a particular emphasis on its speed. We present a completely rewritten version of the sensitive homology search method COMER based on alignment of protein sequence profiles, which is capable of searching big databases even on a lightweight laptop. By harnessing the power of CUDA-enabled GPUs, it is up to 20 times faster than HHsearch

MotivationIn the analysis of high throughput omics data from tissue samples, estimating and accounting for cell composition have been recognized as important steps. High cost, intensive labor requirements and technical limitations hinder the cell composition quantification using cell sorting or single-cell technologies. Computational methods for cell composition estimation are available, but they are

MotivationThird-generation sequencing technologies can sequence long reads that contain as many as 2 million base pairs (bp). These long reads are used to construct an assembly (i.e., the subject’s genome), which is further used in downstream genome analysis. Unfortunately, third-generation sequencing technologies have high sequencing error rates and a large proportion of bps in these long reads are

MotivationDimension reduction techniques are widely used to interpret high-dimensional biological data. Features learned from these methods are used to discover both technical artifacts and novel biological phenomena. Such feature discovery is critically import to large single-cell datasets, where lack of a ground truth limits validation and interpretation. Transfer learning (TL) can be used to relate

MotivationThe field of metagenomics has provided valuable insights into the structure, diversity and ecology within microbial communities. One key step in metagenomics analysis is to assemble reads into longer contigs which are then binned into groups of contigs that belong to different species present in the metagenomic sample. Binning of contigs plays an important role in metagenomics and most available

MotivationFlux balance analysis (FBA) based bilevel optimisation has been a great success in redesigning metabolic networks for biochemical overproduction. To date, many computational approaches have been developed to solve the resulting bilevel optimisation problems. However, most of them are of limited use due to biased optimality principle, poor scalability with the size of metabolic networks, potential

MotivationTechnological advances in metatranscriptomics have enabled a deeper understanding of the structure and function of microbial communities. “Total RNA” metatranscriptomics, sequencing of total reverse transcribed RNA, provides a unique opportunity to investigate both the structure and function of active microbial communities from all three domains of life simultaneously. A major step of this

SummaryThe R/Bioconductor package primirTSS is a fast and convenient tool that allows implementation of the analytical method to identify transcription start sites of microRNAs by integrating ChIP-seq data of H3K4me3 and Pol II. It further ensures the precision by employing the conservation score and sequence features. The tool showed a good performance when using H3K4me3 or Pol II Chip-seq data alone

MotivationPolyproline II (PPII) is a common conformation, comparable to α-helix and β-sheet and is a candidate for being the most prevalent secondary structure. PPII, recently termed with a more generic name – κ-helix, adopts a left-handed structure with 3-fold rotational symmetry. Lately, a new type of binding mechanism – the helical lock and key model was introduced in SH3-domain complexes, where

MotivationMultiple sequence alignment (MSA) is important and challenging problem of computational biology. Most of the existing methods can only provide a short length multiple alignments in an acceptable time. Nevertheless, when the researchers confront the genome size in the multiple alignments, the process has required a huge processing space/time. Accordingly, using the method that can align genome

While many quantitative structure-activity relationship (QSAR) models are trained and evaluated for their predictive merits, understanding what models have been learning is of critical importance. However, the interpretation and visualization of QSAR model results remain challenging, especially for ‘black box’ models such as deep neural network (DNN). Here we take a step forward to interpret the learned

SummaryThe flood of recent cancer genomic data requires a coherent model that can sort out the findings to systematically explain clonal evolution and the resultant intra-tumor heterogeneity (ITH). Here, we present a new mathematical model designed to computationally simulate the evolution of cancer cells. The model connects the well-known hallmarks of cancer with the specific mutational states of