Assembly of 43 human Y chromosomes reveals extensive complexity and variation.

The prevalence of highly repetitive sequences within the human Y chromosome has prevented its complete assembly to date1 and led to its systematic omission from genomic analyses. Here we present de novo assemblies of 43 Y chromosomes spanning 182,900 years of human evolution and report considerable diversity in size and structure. Half of the male-specific euchromatic region is subject to large inversions with a greater than twofold higher recurrence rate compared with all other chromosomes2. Ampliconic sequences associated with these inversions show differing mutation rates that are sequence context dependent, and some ampliconic genes exhibit evidence for concerted evolution with the acquisition and purging of lineage-specific pseudogenes. The largest heterochromatic region in the human genome, Yq12, is composed of alternating repeat arrays that show extensive variation in the number, size and distribution, but retain a 1:1 copy-number ratio. Finally, our data suggest that the boundary between the recombining pseudoautosomal region 1 and the non-recombining portions of the X and Y chromosomes lies 500 kb away from the currently established1 boundary. The availability of fully sequence-resolved Y chromosomes from multiple individuals provides a unique opportunity for identifying new associations of traits with specific Y-chromosomal variants and garnering insights into the evolution and function of complex regions of the human genome.

Curvature-mediated rapid extravasation and penetration of nanoparticles against interstitial fluid pressure for improved drug delivery.

Elevated interstitial fluid pressure (IFP) within pathological tissues (e.g., tumors, obstructed kidneys, and cirrhotic livers) creates a significant hindrance to the transport of nanomedicine, ultimately impairing the therapeutic efficiency. Among these tissues, solid tumors present the most challenging scenario. While several strategies through reducing tumor IFP have been devised to enhance nanoparticle delivery, few approaches focus on modulating the intrinsic properties of nanoparticles to effectively counteract IFP during extravasation and penetration, which are precisely the stages obstructed by elevated IFP. Herein, we propose an innovative solution by engineering nanoparticles with a fusiform shape of high curvature, enabling efficient surmounting of IFP barriers during extravasation and penetration within tumor tissues. Through experimental and theoretical analyses, we demonstrate that the elongated nanoparticles with the highest mean curvature outperform spherical and rod-shaped counterparts against elevated IFP, leading to superior intratumoral accumulation and antitumor efficacy. Super-resolution microscopy and molecular dynamics simulations uncover the underlying mechanisms in which the high curvature contributes to diminished drag force in surmounting high-pressure differentials during extravasation. Simultaneously, the facilitated rotational movement augments the hopping frequency during penetration. This study effectively addresses the limitations posed by high-pressure impediments, uncovers the mutual interactions between the physical properties of NPs and their environment, and presents a promising avenue for advancing cancer treatment through nanomedicine.

Steering the Reconstruction of Oxide-Derived Cu by Secondary Metal for Electrosynthesis of n-Propanol from CO.

As fuel and an important chemical feedstock, n-propanol is highly desired in electrochemical CO2/CO reduction on Cu catalysts. However, the precise regulation of the Cu localized structure is still challenging and poorly understood, thus hindering the selective n-propanol electrosynthesis. Herein, by decorating Au nanoparticles (NPs) on CuO nanosheets (NSs), we present a counterintuitive transformation of CuO into undercoordinated Cu sites locally around Au NPs during CO reduction. In situ spectroscopic techniques reveal the Au-steered formation of abundant undercoordinated Cu sites during the removal of oxygen on CuO. First-principles accuracy molecular dynamic simulation demonstrates that the localized Cu atoms around Au tend to rearrange into disordered layer rather than a Cu (111) close-packed plane observed on bare CuO NSs. These Au-steered undercoordinated Cu sites facilitate CO binding, enabling selective electroreduction of CO into n-propanol with a high Faradaic efficiency of 48% in a flow cell. This work provides new insight into the regulation of the oxide-derived catalysts reconstruction with a secondary metal component.

Einstein-Stokes relation for small bubbles at the nanoscale.

As the physicochemical properties of ultrafine bubble systems are governed by their size, it is crucial to determine the size and distribution of such bubble systems. At present, the size or size distribution of nanometer-sized bubbles in suspension is often measured by either dynamic light scattering or the nanoparticle tracking analysis. Both techniques determine the bubble size via the Einstein-Stokes equation based on the theory of the Brownian motion. However, it is not yet clear to which extent the Einstein-Stokes equation is applicable for such ultrafine bubbles. In this work, using atomic molecular dynamics simulation, we evaluate the applicability of the Einstein-Stokes equation for gas nanobubbles with a diameter less than 10 nm, and for a comparative analysis, both vacuum nanobubbles and copper nanoparticles are also considered. The simulation results demonstrate that the diffusion coefficient for rigid nanoparticles in water is found to be highly consistent with the Einstein-Stokes equation, with slight deviation only found for nanoparticle with a radius less than 1 nm. For nanobubbles, including both methane and vacuum nanobubbles, however, large deviation from the Einstein-Stokes equation is found for the bubble radius larger than 3 nm. The deviation is attributed to the deformability of large nanobubbles that leads to a cushioning effect for collision-induced bubble diffusion.

An accurate interatomic potential for the TiAlNb ternary alloy developed by deep neural network learning method.

The complex phase diagram and bonding nature of the TiAl system make it difficult to accurately describe its various properties and phases by traditional atomistic force fields. Here, we develop a machine learning interatomic potential with a deep neural network method for the TiAlNb ternary alloy based on a dataset built by first-principles calculations. The training set includes bulk elementary metals and intermetallic structures with slab and amorphous configurations. This potential is validated by comparing bulk properties-including lattice constant and elastic constants, surface energies, vacancy formation energies, and stacking fault energies-with their respective density functional theory values. Moreover, our potential could accurately predict the average formation energy and stacking fault energy of γ-TiAl doped with Nb. The tensile properties of γ-TiAl are simulated by our potential and verified by experiments. These results support the applicability of our potential under more practical conditions.

IGFBP7 Fuels the Glycolytic Metabolism in B-Cell Precursor Acute Lymphoblastic Leukemia by Sustaining Activation of the IGF1R-Akt-GLUT1 Axis.

Increased glycolytic metabolism plays an important role in B-cell precursor Acute Lymphoblastic Leukemia (BCP-ALL). We previously showed that IGFBP7 exerts mitogenic and prosuvival effects in ALL by promoting IGF1 receptor (IGF1R) permanence on the cell surface, thus prolonging Akt activation upon IGFs/insulin stimulation. Here, we show that sustained activation of the IGF1R-PI3K-Akt axis concurs with GLUT1 upregulation, which enhances energy metabolism and increases glycolytic metabolism in BCP-ALL. IGFBP7 neutralization with a monoclonal antibody or the pharmacological inhibition of the PI3K-Akt pathway was shown to abrogate this effect, restoring the physiological levels of GLUT1 on the cell surface. The metabolic effect described here may offer an additional mechanistic explanation for the strong negative impact seen in ALL cells in vitro and in vivo after the knockdown or antibody neutralization of IGFBP7, while reinforcing the notion that it is a valid target for future therapeutic interventions.

Synthesis of Nickel Nitride-Based 1D/0D Heterostructure via a Morphology-Inherited Nitridation Strategy for Efficient Electrocatalytic Hydrogen Evolution.

The fabrication of heterostructures has inspired extensive interest in promoting the performance of solar cells or solar fuel production, but it is still challenging for nitrides to prepare structurally ordered heterostructures. Herein, one nickel nitride-based heterostructure composed of 1D Ni0.2 Mo0.8 N nanorods and 0D Ni3 N nanoparticles (denoted as NiMoN/NiN) is reported to exhibit significantly promoted hydrogen evolution reaction performance in both alkaline and neutral media. In particular, the optimal overpotential of the NiMoN/NiN sample at 10 mA cm-2 in 1 m KOH is 49 mV. The successful fabrication of 1D/0D heterostructures is mainly ascribed to morphology-inherited nitridation of 1D oxide precursor (denoted as NiMoO-NRs) in situ grown on Ni foam surface, and attributed to strong Lewis acid-base interaction that renders the Ni2+ ions emitted from the oxide precursor to well coordinate with NH3 for the formation of Ni3 N nanoparticles during the nitridation process. It is theoretically and experimentally demonstrated that the special 1D/0D heterostructure provides tandem active phases Ni0.2 Mo0.8 N and Ni3 N for synergistic promotion in lowering the activation energy of H2 O dissociation and optimizing the adsorption energy of H, respectively. This work may open a new avenue for developing highly active tandem electrocatalysts for promising renewable energy conversion.

Cofactor-free oxidase-mimetic nanomaterials from self-assembled histidine-rich peptides.

Natural oxidases mainly rely on cofactors and well-arranged amino acid residues for catalysing electron-transfer reactions but suffer from non-recovery of their activity upon externally induced protein unfolding. However, it remains unknown whether residues at the active site can catalyse similar reactions in the absence of the cofactor. Here, we describe a series of self-assembling, histidine-rich peptides, as short as a dipeptide, with catalytic function similar to that of haem-dependent peroxidases. The histidine residues of the peptide chains form periodic arrays that are able to catalyse H2O2 reduction reactions efficiently through the formation of reactive ternary complex intermediates. The supramolecular catalyst exhibiting the highest activity could be switched between inactive and active states without loss of activity for ten cycles of heating/cooling or acidification/neutralization treatments, demonstrating the reversible assembly/disassembly of the active residues. These findings may aid the design of advanced biomimetic catalytic materials and provide a model for primitive cofactor-free enzymes.

Temperature- and rigidity-mediated rapid transport of lipid nanovesicles in hydrogels.

Lipid nanovesicles are widely present as transport vehicles in living organisms and can serve as efficient drug delivery vectors. It is known that the size and surface charge of nanovesicles can affect their diffusion behaviors in biological hydrogels such as mucus. However, how temperature effects, including those of both ambient temperature and phase transition temperature (Tm), influence vehicle transport across various biological barriers outside and inside the cell remains unclear. Here, we utilize a series of liposomes with different Tm as typical models of nanovesicles to examine their diffusion behavior in vitro in biological hydrogels. We observe that the liposomes gain optimal diffusivity when their Tm is around the ambient temperature, which signals a drastic change in the nanovesicle rigidity, and that liposomes with Tm around body temperature (i.e., ∼37 °C) exhibit enhanced cellular uptake in mucus-secreting epithelium and show significant improvement in oral insulin delivery efficacy in diabetic rats compared with those with higher or lower Tm Molecular-dynamics (MD) simulations and superresolution microscopy reveal a temperature- and rigidity-mediated rapid transport mechanism in which the liposomes frequently deform into an ellipsoidal shape near the phase transition temperature during diffusion in biological hydrogels. These findings enhance our understanding of the effect of temperature and rigidity on extracellular and intracellular functions of nanovesicles such as endosomes, exosomes, and argosomes, and suggest that matching Tm to ambient temperature could be a feasible way to design highly efficient nanovesicle-based drug delivery vectors.

High-Strength Plus Reversible Supramolecular Adhesives Achieved by Regulating Intermolecular PtII ⋠⋠⋠PtII Interactions.

Surface adhesion has a great contradiction in high strength and good reversibility given their mutually exclusive requirements of fixed crosslinked networks and dynamic chain motion. Herein, we demonstrate a supramolecular organoplatinum(II) adhesive system regulated by intermolecular PtII ⋅⋅⋅PtII interactions that can simultaneously achieve high-strength and excellent reversible adhesion to various substrates. Upon alternating temperature, the assembly of suitably substituted organoplatinum(II) molecules can switch between well-ordered and disordered states via tuning PtII ⋅⋅⋅PtII interactions, resulting in stable reversible adhesion even after 100 cycles with a robust strength of ≈1.25 MPa and a large on-off ratio of ≈25. Along with the switch of PtII ⋅⋅⋅PtII contacts, the surface adhesion of organoplatinum(II) adhesives can be monitored by their changes in electrical signals. This study will open up new inspirations for developing high-performance reversible adhesives.

A parallelized strategy for epistasis analysis based on Empirical Bayesian Elastic Net models.

MOTIVATION: Epistasis 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 datasets. One is that epistasis analysis will induce over-fitting of an over-saturated model with the high-dimensionality of a genomic dataset. Therefore, the problem of identifying epistasis demands efficient statistical methods. The second barrier comes from the intensive computing time for epistasis analysis, even when the appropriate model and data are specified. RESULTS: In this study, we combine statistical techniques and computational techniques to scale up epistasis analysis using Empirical Bayesian Elastic Net (EBEN) models. Specifically, we first apply a matrix manipulation strategy for pre-computing the correlation matrix and pre-filter to narrow down the search space for epistasis analysis. We then develop a parallelized approach to further accelerate the modeling process. Our experiments on synthetic and empirical genomic data demonstrate that our parallelized methods offer tens of fold speed up in comparison with the classical EBEN method which runs in a sequential manner. We applied our parallelized approach to a yeast dataset, and we were able to identify both main and epistatic effects of genetic variants associated with traits such as fitness. AVAILABILITY AND IMPLEMENTATION: The software is available at github.com/shilab/parEBEN.

Interplay between cooperativity of intercellular receptor-ligand binding and coalescence of nanoscale lipid clusters in adhering membranes.

Adhesion of biological cells is mediated by the specific binding of receptors and ligands which are typically large proteins spanning through the plasma membranes of the contacting cells. The receptors and ligands can exhibit affinity for nanoscale lipid clusters that form within the plasma membrane. A central question is how these nanoscale lipid clusters physically affect and respond to the receptor-ligand binding during cell adhesion. Within the framework of classical statistical mechanics we find that the receptor-ligand binding reduces the threshold energy for lipid clusters to coalesce into mesoscale domains by up to ∼50%, and that the formation of these domains induces significant cooperativity of the receptor-ligand binding. The interplay between the receptor-ligand binding cooperativity and the lipid domain formation manifests acute sensitivity of the membrane system to changes in control parameters. This sensitivity can be crucial in cell signaling and immune responses.

The role of supported dual-atom on graphitic carbon nitride for selective and efficient CO2electrochemical reduction.

The electrochemical reduction of CO2into value-added fuels and chemicals using single atom (SACs) or dual-atom catalysts (DACs) has been extensively studied, but the reaction mechanism and design rules are still unclear. Here, we studied the role of dual-metal atoms on graphite carbon nitride (M1M2@g-CN, M1M2 = CuCu, FeFe, RuRu, RuCu, RuFe, CuFe) for selective and efficient CO2electrochemical reduction based on density functional theory. Our results show that CO2RR on RuRu@g-CN catalyst prefers the *COOH pathway, while for CuCu@g-CN, FeFe@g-CN, RuCu@g-CN, RuFe@g-CN, CuFe@g-CN catalysts, the *OCHO pathway is more suitable. Among all the DACs combinations, we found that RuCu@g-CN and RuFe@g-CN are the most promising electrocatalysts for CO2RR with a lower limiting potential, which is attributed to the synergistic effect of different O- and C-affinity of the heterocenters in DACs. The selectivity of RuCu@g-CN and RuFe@g-CN to the production of CH4is better than that of H2evolution. In addition, we also found that the adsorption free energy of intermediate on heteroatomic DACs can be predicted by those on homoatomic DACs, which can be used to further predict the limiting potential.

The RNA structurome in the asexual blood stages of malaria pathogen plasmodium falciparum.

Plasmodium falciparum is a deadly human pathogen responsible for the devastating disease called malaria. In this study, we measured the differential accumulation of RNA secondary structures in coding and non-coding transcripts from the asexual developmental cycle in P. falciparum in human red blood cells. Our comprehensive analysis that combined high-throughput nuclease mapping of RNA structures by duplex RNA-seq, SHAPE-directed RNA structure validation, immunoaffinity purification and characterization of antisense RNAs collectively measured differentially base-paired RNA regions throughout the parasite's asexual RBC cycle. Our mapping data not only aligned to a diverse pool of RNAs with known structures but also enabled us to identify new structural RNA regions in the malaria genome. On average, approximately 71% of the genes with secondary structures are found to be protein coding mRNAs. The mapping pattern of these base-paired RNAs corresponded to all regions of mRNAs, including the 5' UTR, CDS and 3' UTR as well as the start and stop codons. Histone family genes which are known to form secondary structures in their mRNAs and transcripts from genes which are important for transcriptional and post-transcriptional control, such as the unique plant-like transcription factor family, ApiAP2, DNA-/RNA-binding protein, Alba3 and proteins important for RBC invasion and malaria cytoadherence also showed strong accumulation of duplex RNA reads in various asexual stages in P. falciparum. Intriguingly, our study determined stage-specific, dynamic relationships between mRNA structural contents and translation efficiency in P. falciparum asexual blood stages, suggesting an essential role of RNA structural changes in malaria gene expression programs. Abbreviations: CDS: Coding Sequence; DNA: Deoxyribonucleic Acid; dsRNA: double-stranded RNA; IDC: Intra-erythrocytic Developmental Cycle (IDC); m6A: N6-methyladenosine; mRNA: Messenger RNA; ncRNA: Non-coding RNA; RBC: Red Blood cells; RBP: RNA-Binding Protein; REC: Relative Expression Counts; RNA-seq: RNA-sequencing; RNA: Ribonucleic Acid; RNP: Ribonucleoprotein; RPKM: Reads Per Kilobase of transcript Per Million; rRNA: Ribosomal RNA 16. RUFs: RNAs of Unknown Function; SHAPE: Selective 2'-hydroxyl acylation analysed by primer extension; snoRNA: Small Nucleolar RNA; snRNA: Small Nuclear RNA; SRP-RNA: Signal Recognition Particle RNA; ssRNA: (Single-stranded RNA); TE: Translation Efficiency; tRNA: transfer RNA; UTR: Untranslated Region.

An integrated map of structural variation in 2,504 human genomes.

Structural variants are implicated in numerous diseases and make up the majority of varying nucleotides among human genomes. Here we describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which we constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations. Analysing this set, we identify numerous gene-intersecting structural variants exhibiting population stratification and describe naturally occurring homozygous gene knockouts that suggest the dispensability of a variety of human genes. We demonstrate that structural variants are enriched on haplotypes identified by genome-wide association studies and exhibit enrichment for expression quantitative trait loci. Additionally, we uncover appreciable levels of structural variant complexity at different scales, including genic loci subject to clusters of repeated rearrangement and complex structural variants with multiple breakpoints likely to have formed through individual mutational events. Our catalogue will enhance future studies into structural variant demography, functional impact and disease association.

Diffusion of Nanoparticles with Activated Hopping in Crowded Polymer Solutions.

A long-distance hop of diffusive nanoparticles (NPs) in crowded environments was commonly considered unlikely, and its characteristics remain unclear. In this work, we experimentally identify the occurrence of the intermittent hops of large NPs in crowded entangled poly(ethylene oxide) (PEO) solutions, which are attributed to thermally induced activated hopping. We show that the diffusion of NPs in crowded solutions is considered as a superposition of the activated hopping and the reptation of the polymer solution. Such activated hopping becomes significant when either the PEO molecular weight is large enough or the NP size is relatively small. We reveal that the time-dependent non-Gaussianity of the NP diffusion is determined by the competition of the short-time relaxation of a polymer entanglement strand, the activated hopping, and the long-time reptation. We propose an exponential scaling law τhop/τe ∼ exp(d/dt) to characterize the hopping time scale, suggesting a linear dependence of the activated hopping energy barrier on the dimensionless NP size. The activated hopping motion can only be observed between the onset time scale of the short-time relaxation of local entanglement strands and the termination time scale of the long-time relaxation. Our findings on activated hopping provide new insights into long-distance transportation of NPs in crowded biological environments, which is essential to the delivery and targeting of nanomedicines.

Enhanced Transport of Shape and Rigidity-Tuned α-Lactalbumin Nanotubes across Intestinal Mucus and Cellular Barriers.

Mucus is a viscoelastic biological hydrogel that protects the epithelial surface from penetration by most nanoparticles, which limits the efficiency of oral drug delivery. Pursuing highly efficient, biocompatible, and biodegradable oral drug vehicles is of central importance to the development of promising nanomedicine. Here, we prepared five peptosomes (PSs) with various sizes, shapes, and rigidities based on self-assembly of amphiphilic α-lactalbumin (α-lac) peptides from partial enzymolysis and cross-linking. The mucus permeation of α-lac PSs and release of curcumin (Cur) encapsulated in these PSs were evaluated. Compared with a long nanotube, big nanosphere, small nanosphere, and cross-linked short nanotube, we demonstrated that a short nanotube (SNT) exhibits excellent permeability in mucus, which enables it to arrive at epithelial cells quickly. Besides, SNT exhibits the highest cellular uptake and transmembrane permeability on Caco-2/HT29-MTX (E12) 3D coculture model. In vivo pharmacokinetic evaluation revealed that SNT formulation shows the highest curcumin bioavailability, which is 6.85-folds higher than free Cur. Most importantly, Cur loaded in SNT exhibits the optimum therapeutic efficacy for in vivo treatment of dextran sulfate sodium (DSS)-induced ulcerative colitis. In the end, the mechanism of the high permeability of SNTs through mucus was explained by coarse-grained molecular dynamics simulations, which indicated that short time scale jiggling and flying across pores of mucus network played key roles. These findings revealed the tubular α-lac PSs could be a promising oral drug delivery system targeted to mucosal for improving absorption and bioavailability of hydrophobic bioactive ingredients.

Cancer-Cell-Membrane-Coated Nanoparticles with a Yolk-Shell Structure Augment Cancer Chemotherapy.

Despite rapid advancements in antitumor drug delivery, insufficient intracellular transport and subcellular drug accumulation are still issues to be addressed. Cancer cell membrane (CCM)-camouflaged nanoparticles (NPs) have shown promising potential in tumor therapy due to their immune escape and homotypic binding capacities. However, their efficacy is still limited due to inefficient tumor penetration and compromised intracellular transportation. Herein, a yolk-shell NP with a mesoporous silica nanoparticle (MSN)-supported PEGylated liposome yolk and CCM coating, CCM@LM, was developed for chemotherapy and exhibited a homologous tumor-targeting effect. The yolk-shell structure endowed CCM@LM with moderate rigidity, which might contribute to the frequent transformation into an ellipsoidal shape during infiltration, leading to facilitated penetration throughout multicellular spheroids in vitro (up to a 23.3-fold increase compared to the penetration of membrane vesicles). CCM@LM also exhibited a cellular invasion profile mimicking an enveloped virus invasion profile. CCM@LM was directly internalized by membrane fusion, and the PEGylated yolk (LM) was subsequently released into the cytosol, indicating the execution of an internalization pathway similar to that of an enveloped virus. The incoming PEGylated LM further underwent efficient trafficking throughout the cytoskeletal filament network, leading to enhanced perinuclear aggregation. Ultimately, CCM@LM, which co-encapsulated low-dose doxorubicin and the poly(ADP-ribose) polymerase inhibitor, mefuparib hydrochloride, exhibited a significantly stronger antitumor effect than the first-line chemotherapeutic drug Doxil. Our findings highlight that NPs that can undergo facilitated tumor penetration and robust intracellular trafficking have a promising future in cancer chemotherapy.

Bamboo-like π-Nanotubes with Tunable Helicity and Circularly Polarized Luminescence.

We report the fabrication of an exotic bamboo-like π-nanotube via the hierarchical self-assembly of a dipeptide-substituted naphthalenediimide gelator with tunable helicity and circularly polarized luminescence (CPL). It was found that in the presence of trifluoroacetic acid (TFA) the gelator molecules self-assembled into a bamboo-like π-nanotube, which is composed of truncated nanocones and CPL active. When defining the diameter ratio of the lower to upper edge of each nanocone as a parameter to express the helicity of different nanotubes, it was found that both the helicity and CPL of these nanotubes can be adjusted by the amount of TFA. Moreover, the helicity of the nanotube can be conveyed to the achiral quantum dots (QDs) and produce a hybrid nanotube/QDs CPL active materials with adjustable dissymmetry factor. This work finds a new type self-assembled bamboo-like π-nanotube and unveils their helicity and CPL control.

Accelerating bioinformatics research with International Conference on Intelligent Biology and Medicine 2020.

The International Association for Intelligent Biology and Medicine (IAIBM) is a nonprofit organization that promotes intelligent biology and medical science. It hosts an annual International Conference on Intelligent Biology and Medicine (ICIBM), which was initially established in 2012. Due to the coronavirus (COVID-19) pandemic, the ICIBM 2020 was held for the first time as a virtual online conference on August 9 to 10. The virtual conference had ~ 300 registered participants and featured 41 online real-time presentations. ICIBM 2020 received a total of 75 manuscript submissions, and 12 were selected to be published in this special issue of BMC Bioinformatics. These 12 manuscripts cover a wide range of bioinformatics topics including network analysis, imaging analysis, machine learning, gene expression analysis, and sequence analysis.