bluuebunny/crossref_metadata_2025 huggingface dataset:
Prediction of IFNγ Regulated Gene Transcription
Authors: Liu Hong , Ge Nanxiang , Yu Kin-Tak , Krolikowski David , Zilberstein Asher , Hahn Chang S.
Published: January 2025

IFNγ, a cytokine promoting cell-mediated immunity and antiviral effects, regulates the expression of a large set of genes involved in the immune response. Based on logistic regression, an in silico model for predicting IFNγ regulated transcription has been developed by scoring the transcription factor binding sites on the putative promoters of regulated versus not regulated genes derived from the microarray data of IFNγ treated human macrophages. The model effectively discriminates the transcription factor binding sites that confer responsiveness to IFNγ from those that do not. The model has 65% true positive and 22% false positive rates when evaluated on a small validation set. In order to identify potential IFNγ regulated genes in the whole genome, the model has been used to screen 13,668 promoter pairs of human-mouse orthologs/homologs from Ensembl, and 1,387 of them were predicted to be potentially regulated by IFNγ. In the pilot experiment, the regulation pattern of a subset of predicted genes that were not detected by microarray approach was evaluated by quantitative PCR. The results for the four novel genes, which are up regulated by IFNγ in human macrophages and identified by this approach, are described in the present communication.
In Silico Exploration of the Fructose-6- Phosphate Phosphorylation Step in Glycolysis: Genomic Evidence of the Coexistence of an Atypical ATP-Dependent Along with a PPi-Dependent Phosphofructokinase in Propionibacterium freudenreichii subsp. shermanii
Authors: Meurice Guillaume , Deborde Catherine , Jacob Daniel , Falentin Hélène , Boyaval Patrick , Dimova Diliana
Published: January 2025

We performed a detailed bioinformatic study of the catalytic step of fructose-6-phosphate phosphorylation in glycolysis based on the raw genomic draft of Propionibacterium freudenreichii subsp. shermanii (P. shermanii) ATCC9614 [Meurice et al., 2004]. Our results provide the first in silico evidence of the coexistence of genes coding for an ATP-dependent phosphofructokinase (ATP-PFK) and a PPi-dependent phosphofructokinase (PPi-PFK), whereas the fructose-1,6-bisphosphatase (FBP) and ADP-dependent phosphofructokinase (ADP-PFK) are absent. The deduced amino acid sequence corresponding to the PPi-PFK (AJ508922) shares 100% similarity with the already characterised propionibacterial protein (P29495; Ladror et al., 1991]. The unexpected ATP-PFK gene (AJ509827) encodes a protein of 373 aa which is highly similar (50% positive residues) along at least 95% of its sequence length to different well-characterised ATP-PFKs. The characteristic PROSITE pattern important for the enzyme function of ATP-PFKs (PS00433) was conserved in the putative ATP-PFK sequence: 8 outof.
An Organizational Model of Transcription Factor Binding Sites for a Histone Promoter in D. melanogaster
Authors: Crayton III Mack E. , Ladd Carll E. , Sommer Martin , Hampikian Gregory , Strausbaugh Linda D.
Published: January 2025

The Drosophila H2A-H2B histone spacer, a small region that functions as a bidirectional promoter for the gene pair, was used as a test sequence for generation of a computationally derived organizational model of transcription factor (TF) binding sites. Expression studies of the spacer revealed that it contains the necessary sequences to confer replication-dependent transcription in partially synchronized cells in culture. Informatics analysis of the spacer uncovered a number of binding sites for specific TFs, none of which had been previously associated with this particular promoter. Each of the TFs in the promoter organizational model are also known to participate in stages of fly development that are characterized by DNA replication and/or cell division, thus providing a biologically functional rationale for an association. Moreover, phylogenetic analysis of the binding sites provides evidence for evolutionary conservation of the essential features of the organizational model. The model, if correct, provides information about the molecules that couple developmental specific demands and histone gene transcription.
Consensus Based Validation of Membrane Porins
Authors: Katta A.V.S.K. Mohan , Marikkannu Rajeshwari , Basaiawmoit Rajiv V. , Krishnaswamy Sankaran
Published: January 2025

Porins are outermembrane β-barrel proteins. They have varied biological functionality ranging from phage receptors, immunogenicity, pathogenicity to apoptosis. However, only a small number has been structurally and functionally characterised. A validation mechanism and a database of porins would be useful for target selection in proteomics and structural genomics work. Here we report a validation mechanism developed for membrane porins. A database server for porins, PRNDS, has been created containing experimentally proven porins and likely putative porins. Each porin is validated and ranked using a weighted scoring system developed based on six, structure and sequence based criteria. The server also predicts possible porins.
Clusters of Proteins in Archaeal and Bacterial Proteomes using Compositional Analysis
Authors: Nandi Tannistha , Brahmachari Samir K. , Kannan Krishnamoorthy , Ramachandran Srinivasan
Published: January 2025

In silico proteomics complements computational genomics in characterizing genome evolution. Here we examine cluster patterns in archaeal and bacterial proteomes using compositional properties of protein sequences in contrast to the traditionally used sequence alignment procedures. Application of standard Principal Component Analysis to the multi-dimensional data identified cluster patterns. Two types of cluster patterns exist in bacterial proteomes. Proteomes of type I have one major cluster with few isolated points in space revealing an underlying largely homogeneous compositional structure. In type II proteomes two clusters of protein distribution were discernible. The two clusters differ in size and were separated from each other although the boundary was somewhat fuzzy. Proteins falling in the major cluster were labeled as 'typical' and proteins of the minor cluster were called 'atypical'. The atypical proteins were mapped to Cluster of Orthologous Groups. Species distribution in COGs maps with respect to atypical proteins illuminated the biological relationships of extreme diversity among the archaeal members and of diversity among bacteria in relation to their niche. Amino acids that were over-represented in the atypical proteins had higher biosynthetic cost compared to 'typical' ribosomal proteins. However, archaea and bacteria economize by preferring the less costly amino acid to others closely related in chemical structure. Further, over-representation of serine in atypical proteins of archaeal members suggests re-examining these proteomes for the presence of Serine/Threonine phosphatases and kinases in Archaea. Our computational procedure can serve as a useful addition to the existing tools for carrying out in silico proteomics.
$STR^{2}$: A Structure to String Approach for Locating G-Box Riboswitch Shapes in Pre-Selected Genes
Authors: Bergig Oriel , Barash Danny , Nudler Evgeny , Kedem Klara
Published: January 2025

Traditional sequence-based search methods such as BLAST and FASTA can be used to identify sequence similarities. Recently, there is a growing interest in performing RNA shape similarity searches inside selected genes to locate RNA structure motifs that are known to possess functionally important roles. For example, in the newly discovered RNA genetic control elements called "riboswitches", the box domain is known to be highly conserved among various bacterial species in both its nucleotide composition and shape. However, in non-bacterial species, shape conservation is likely to become more important than sequence conservation when searching for riboswitch patterns. For this purpose, we present an approach tailored for detecting RNA shape similarities. We extend the Structure to String ( $STR^{2}$ ) method that was initially proposed to locate shape similarities in proteins to identify predicted secondary structures of RNAs. The $STR^{2}$ for RNAs is a translation of a secondary structure to a string of characters, after which known sequence-based search algorithms with an efficient implementation are being used. We validate that the $STR^{2}$ succeeds to locate G-box riboswitches in prokaryotes, as expected. Subsequently we show running examples when attempting to detect G-box riboswitch candidates in eukaryotes.
SPI – Structure Predictability Index for Protein	Sequences
Authors: Brylinski Michal , Konieczny Leszek , Roterman Irena
Published: January 2025

Estimation of structure predictability for a particular protein is difficult. Many methods estimate it in an a posteriori system evaluating the final, native protein structure. The SPI scale is intended to estimate the structure predictability of a {particular} amino acid sequence in an a priori system. A sequence-to-structure library was created based on the complete Protein Data Bank. The tetrapeptide was selected as a unit representing a well-defined structural motif. The early-stage folding structure (a model of which was presented elsewhere) was taken as the object for protein structure classification. Seven structural forms were distinguished for structure classification. The degree of determinability was estimated for the sequence-to-structure and structure-to-sequence relations particularly interesting for threading methods. A comparative analysis of the SPI and Q7 scales with the commonly used SOV and Q3 scales is presented. The complete contingency table, supplementary materials and all the programs used are available on request.
Magmas Gene Structure and Evolution
Authors: Peng Jianbin , Huang Cheng-Han , Short Mary K. , Jubinsky Paul T.
Published: January 2025

Magmas is a nuclear encoded protein found in the mitochondria of mammalian cells. It participates in granulocyte-macrophage-colony stimulating factor (GM-CSF) signaling in hematopoietic cells and has an essential role in invertebrate development. In order to characterize the protein structural features and gene evolution of Magmas, a dataset containing 61 Magmas homologs from 52 species distributed among animals, plants and fungi was analyzed. All Magmas members were found to possess three novel sequence motifs in addition to a conserved leader peptide. Phylogenetic tree and dN/dS rate ratios showed that Magmas was evolutionarily conserved. Analysis of Magmas gene organization demonstrated incremental intron acquisition in plants and vertebrates. Significant genetic diversity in Magmas was observed from kingdom specific amino acid signatures, the presence of predicted signal peptides that target the protein to other intracellular locations besides the mitochondria, and the detection of multiple isoforms in higher animals. These studies demonstrate that Magmas members constitute an important family of conserved proteins having multifunctional activities, and provide a basis for future experiments.
New Assessment of a Structural Alphabet
Authors: de Brevern Alexandre G.
Published: January 2025

A statistical analysis of the Protein Databank (PDB) structures had led us to define a set of small 3D structural prototypes called Protein Blocks (PBs). This structural alphabet includes 16 PBs, each one defined by the (ϕ, ψ) dihedral angles of 5 consecutive residues. Here, we analyze the effect of the enlargement of the PDB on the PBs' definition. The results highlight the quality of the 3D approximation ensured by the PBs. These last could be of great interest in ab initio modeling.
A New Domain Family in the Superfamily of Alkaline	Phosphatases
Authors: Bhadra Rana , Srinivasan Narayanaswamy , Pandit Shashi B.
Published: January 2025

During the course of our large-scale genome analysis a conserved domain, currently detectable only in the genomes of Drosophila melanogaster, Caenorhabditis elegans and Anopheles gambiae, has been identified. The function of this domain is currently unknown and no function annotation is provided for this domain in the publicly available genomic, protein family and sequence databases. The search for the homologues of this domain in the non-redundant sequence database using PSI-BLAST, resulted in identification of distant relationship between this family and the alkaline phosphatase-like superfamily, which includes families of aryl sulfatase, N-acetylgalactosomine-4-sulfatase, alkaline phosphatase and 2,3-bisphosphoglycerate-independent phosphoglycerate mutase (iPGM). The fold recognition procedures showed that this new domain could adopt a similar 3-D fold as for this supefamily. Most of the phosphatases and sulfatases of this superfamily are characterized by functional residues Ser and Cys respectively in the topologically equivalent positions. This functionally important site aligns with Ser/Thr in the members of the new family. Additionally, set of residues responsible for a metal binding site in phosphatases and sulphtases are conserved in the new family. The in-depth analysis suggests that the new family could possess phosphatase activity.
Analysis of Gene Ontology Features in Microarray Data Using the	Proteome BioKnowledge® Library
Authors: Johnson Robin J. , Williams Jennifer M. , Schreiber Barbara M. , Elfe Charles D. , Lennon-Hopkins Kelley L. , Skrzypek Marek S. , White Renee D.
Published: January 2025

Microarray technology has resulted in an explosion of complex, valuable data. Integrating data analysis tools with a comprehensive underlying database would allow efficient identification of common properties among differentially regulated genes. In this study we sought to compare the utility of various databases in microarray analysis. The Proteome BioKnowledge® Library (BKL), a manually curated, proteome-wide compilation of the scientific literature, was used to generate a list of Gene Ontology (GO) Biological Process (BP) terms enriched among proteins involved in cardiovascular disease. Analysis of DNA microarray data generated in a study of rat vascular smooth muscle cell responses revealed significant enrichment in a number of GO BPs that were also enriched among cardiovascular disease-related proteins. Using annotation from LocusLink and chip annotation from the Gene Expression Omnibus yielded fewer enriched cardiovascular disease-associated GO BP terms. Data sets of orthologous genes from mouse and human were generated using the BKL Retriever. Analysis of these sets focusing on BKL Disease annotation, revealed a significant association of these genes with cardiovascular disease. These results and the extensive presence of experimental evidence for BKL GO and Disease features, underscore the benefits of using this database for microarray analysis.
KEGG-Based Pathway Visualization Tool for Complex Omics Data
Authors: Arakawa Kazuharu , Kono Nobuaki , Yamada Yohei , Mori Hirotada , Tomita Masaru
Published: January 2025

Pathway-level visualization of omics data provides an essential means for systems biology, to capture the systematic properties of the inner activities of cells. Here we describe a web-based resource consisting of a web-application for the visualization of complex omics data onto KEGG pathways to overview all entities in the context of cellular pathways, and databases created with the software to visualize a series of microarray data. The web-application accepts transcriptome, proteome, metabolome, or the combination of these data as input, and because of this scalability it is advantageous for the visualization of cell simulation results. The web server can be accessed at http://www.g-language.org/data/marray/.
FASSM: Enhanced Function Association in Whole Genome Analysis	Using Sequence and Structural Motifs
Authors: Gaurav Kumar , Gupta Nitin , Sowdhamini Ramanathan
Published: January 2025

We present an algorithm to detect remote homology, which arises through circular permutation and discontinuous domains. It is also helpful in detecting small domain proteins that are characterized by few conserved residues. The input to the algorithm is a set of multiply aligned protein sequence profiles. This method, coded as FASSM, examines the sequence conservation and positions of protein family signatures or motifs for the annotation of protein sequences and to facilitate the analysis of their domains. The overall coverage of FASSM is 93% in comparison to other validation tools like HMM and IMPALA. The method is especially useful for difficult relationships such as discontinuous domains during whole-genome surveys and is demonstrated to perform accurate family associations at sequence identities as low as 15%.

Availability: Available upon request from the authors.
Ontology Based Standardization of Petri Net Modeling for Signaling	Pathways
Authors: Takai-Igarashi Takako
Published: January 2025

Taking account of the great availability of Petri nets in modeling and analyzing large complicated signaling networks, semantics of Petri nets is in need of systematization for the purpose of consistency and reusability of the models. This paper reports on standardization of units of Petri nets on the basis of an ontology that gives an intrinsic definition to the process of signaling in signaling pathways.
Signal-Theoretical DNA Similarity Measure Revealing Unexpected	Similarities of E. coli Promoters
Authors: Deyneko Igor V. , Kel Alexander E. , Blöcker Helmut , Kauer Gerhard
Published: January 2025

We present an implementation of the signal theory-based approach for detection of novel types of DNA similarity which are based on physical properties of DNA. Systematic study of the sensitivity of the new similarity measure revealed qualitative differences to letter-based similarity. A variety of physical parameters of DNA double strands, which in a straightforward way reflect different kinds of information hidden behind the primary structure of DNA, showed a wide range of recognition power of the signal similarity measure. We applied the novel DNA similarity measure for the analysis of promoters of E. coli genes. We found that promoter similarities revealed by our approach correlate with their transcription regulatory responsivenesses to different antibiotic and osmotic treatments. Accelerated by special hardware for fast Fourier transformations, the method is easily applicable for the analysis of entire eukaryotic genomes in minutes.
Comparative Analysis of Methodologies for the Detection of	Horizontally Transferred Genes: A Reassessment of First-Order Markov	Models
Authors: Cortez Diego Q. , Lazcano Antonio , Becerra Arturo
Published: January 2025

With the advent of larger genome databases detection of horizontal gene transfer events has been transformed into an increasingly important issue. Here we present a simple theoretical analysis based on the in silico artificial addition of known foreign genes from different prokaryotic groups into the genome of Escherichia coli K12 MG1655. Using this dataset as a control, we have tested the efficiency of four methodologies commonly employed to detect HTG (Horizontally transferred genes), which are based on (a) the codon adaptation index, codon usage, and GC percentage (CAI/GC); (b) a distributional profile (DP) approach made by a gene search in the closely related phylogenetic genomes; (c) a Bayesian model (BM); and (d) a first-order Markov model (MM). All methods exhibit limitations although, as shown here, the BM and the MM are better approximations. Moreover, the MM has demonstrated a more accurate rate of detections when genes from closely related organisms are evaluated. The application of the MM to detect recently transferred genes in the genomes of E. coli strains K12 MG1655, O157 EDL933, and Salmonella typhimurium, shows that these organisms have undergone a rather significant amount of HTG, most of which appear to be pseudogenes. Few of these sequences that have undergone HGT appear to have well defined functions and may be involved in the organism's adaptation.
DoD: Database of Databases – Updated Molecular Biology	Databases
Authors: Babu P. Ajay , Boddepalli Radha , Lakshmi V. Vasantha , Rao G. Nageswara
Published: January 2025

Database of Databases (DoD) is a collection of molecular biology databases extracted from Nucleic Acids Research, 2005 Database issue. DoD is constructed using javascript and html code. The 14 categories of 719 databases are provided with a search option, keyword help and database description linked to respective pages. Keyword help lists the search strings used to perform an individual search against categorized databases. Database description provides brief information about the database with a link to full-text article and main web page. DoD is available online and can be accessed at http://www.progenebio.in/DoD/DoD.htm.
u-Genome: A Database on Genome Design in Unicellular Genomes
Authors: Sakharkar Kishore Ramaji , Chaturvedi Iti , Chow Vincent T.K. , Kwoh Chee Keong , Kangueane Pandjassarame , Sakharkar Meena Kishore
Published: January 2025

Unicellular eukaryotes were among the first ones to be selected for complete genome sequencing because of the small size of their genomes and their interactions with humans and a broad range of animals and plants. Currently, ten completely sequenced unicellular genome sequences have been publicly released and as the number of available unicellular genomes increases, comparative genomics analysis within this group of organisms becomes more and more instructive. However, such an analysis is difficult to carry out without a suitable platform gathering not only the original annotations but also relevant information available in public databases or obtained by applying common bioinformatics methods. With the aim of solving these difficulties, we have developed a web-accessible database named u-Genome, the unicellular genome design database. The database is unique in featuring three datasets namely (1) orthologous proteins (2) paralogous proteins and (3) statistical distributions on exons, introns, intergenic DNA and correlations between them. A tool, Uniview, designed to visualize the gene structures for individual genes in the genome is also integrated. This database is of importance in understanding unicellular genome design and architecture and evolution related studies. The database is available through a web interface at http://sege.ntu.edu.sg/wester/ugenome.
Simulation-Based Validation of the p53 Transcriptional Activity	with Hybrid Functional Petri Net
Authors: Doi Atsushi , Nagasaki Masao , Matsuno Hiroshi , Miyano Satoru
Published: January 2025

MDM2 and p19ARF are essential proteins in cancer pathways forming a complex with protein p53 to control the transcriptional activity of protein p53. It is confirmed that protein p53 loses its transcriptional activity by forming the functional dimer with protein MDM2. However, it is still unclear that protein p53 keeps its transcriptional activity when it forms the trimer with proteins MDM2 and p19ARF. We have observed mutual behaviors among genes p53, MDM2, p19ARF and their products on a computational model with hybrid functional Petri net (HFPN) which is constructed based on information described in the literature. The simulation results suggested that protein p53 should have the transcriptional activity in the forms of the trimer of proteins p53, MDM2, and p19ARF. This paper also discusses the advantages of HFPN based modeling method in terms of pathway description for simulations.
In Silico Identification of Potential	Therapeutic Targets in the Human Pathogen Helicobacter	Pylori
Authors: Dutta Anirban , Singh Shashi Kr. , Ghosh Payel , Mukherjee Runni , Mitter Sayak , Bandyopadhyay Debashis
Published: January 2025

Availability of genome sequences of pathogens has provided a tremendous amount of information that can be useful in drug target and vaccine target identification. One of the recently adopted strategies is based on a subtractive genomics approach, in which the subtraction dataset between the host and pathogen genome provides information for a set of genes that are likely to be essential to the pathogen but absent in the host. This approach has been used successfully in recent times to identify essential genes in Pseudomonas aeruginosa. We have used the same methodology to analyse the whole genome sequence of the human gastric pathogen Helicobacter pylori. Our analysis revealed that out of the 1590 coding sequences of the pathogen, 40 represent essential genes that have no human homolog. We have further analysed these 40 genes by the protein sequence databases to list some 10 genes whose products are possibly exposed on the pathogen surface. This preliminary work reported here identifies a small subset of the Helicobacter proteome that might be investigated further for identifying potential drug and vaccine targets in this pathogen.
CorrXpression – Identification of Significant	Groups of Genes and Experiments by Means of Correspondence Analysis and Ratio	Analysis
Authors: Wessel Ralf , Foos Volker , Aspelmeier Allan , Jürgens Martin , Graessmann Adolf , Klein Andreas
Published: January 2025

CorrXpression is a stand-alone desktop application for the identification of significant genes within collections of microarrays. The software combines three methods in two steps of analysis: correspondence analysis (CA), ratio analysis and correlation analysis. The graphical interface of CorrXpression visualizes the result of the CA with a biplot and the expression of selected genes in dependency of the experiments as bar diagrams. The CA-plot is an excellent tool for visualization and evaluation of data and results of ratio analysis and correlation analysis. The input data are selected from a database or from appropriate ASCII files.
DNA Motifs and Sequence Periodicities
Authors: Kumar Lokesh , Futschik Matthias , Herzel Hanspeter
Published: January 2025

Genomic DNA sequences contain a wealth of information about the bendability and curvature of the DNA molecule. For example, the well-known 10–11 bp periodicities within genomes can be attributed to supercoiled structures or wrapping around nucleosomes. Such periodic signals have previously been examined mainly based on mono- or dinucleotide correlations. In this study, we generalize this approach and analyze correlation functions of longer motifs such as tetramers or poly(A) sequences. Periodically placed motifs may indicate regular protein binding or curvature signals. We detected various periodic signals e.g. strong 10–11 bp oscillations of periodically placed poly(A), poly(T) or poly(W) stretches. These observations lead to a new view on the intensively studied 10–11 bp periodicities.
Analyzing Stationary States of Gene Regulatory Network Using Petri	Nets
Authors: Gambin Anna , Lasota Sıawomir , Rutkowski Michaı
Published: January 2025

We introduce and formally define the notion of a stationary state for Petri nets. We also propose a fully automatic method for finding such states. The procedure makes use of the Presburger arithmetic to describe all the stationary states. Finally we apply this novel approach to find stationary states of a gene regulatory network describing the flower morphogenesis of A. thaliana. This shows that the proposed method can be successfully applied in the study of biological systems.
Prediction of C$^{α}$-H·O and	C$^{α}$-H·π Interactions in Proteins Using	Recurrent Neural Network
Authors: Kaur Harpreet , Raghava Gajendra Pal Singh
Published: January 2025

In this study, an attempt has been made to develop a method for predicting weak hydrogen bonding interactions, namely, C $^{α}$ -H·O and C $^{α}$ -H·π interactions in proteins using artificial neural network. Both standard feed-forward neural network (FNN) and recurrent neural networks (RNN) have been trained and tested using five-fold cross-validation on a non-homologous dataset of 2298 protein chains where no pair of sequences has more than 25% sequence identity. It has been found that the prediction accuracy varies with the separation distance between donor and acceptor residues. The maximum sensitivity achieved with RNN for C $^{α}$ -H·O is 51.2% when donor and acceptor residues are four residues apart (i.e. at Δ $_{D-A}$ =4) and for C $^{α}$ -H·π is 82.1% at Δ $_{D-A}$ =3. The performance of RNN is increased by 1–3% for both types of interactions when PSIPRED predicted protein secondary structure is used. Overall, RNN performs better than feed-forward networks at all separation distances between donor-acceptor pair for both types of interactions. Based on the observations, a web server CHpredict (available at http://www.imtech.res.in/raghava/chpredict/) has been developed for predicting donor and acceptor residues in C $^{α}$ -H·O and C $^{α}$ -H·π interactions in proteins.
Social Behavior of The Yeast Protein-Protein Interaction	Network
Authors: Seshasayee Aswin Sai Narain
Published: January 2025

Protein-protein interaction networks are useful in contextual annotation of protein function and in general to achieve a system-level understanding of cellular behavior. This work reports on the social behavior of the yeast protein-protein interaction network and concludes that it is non-random. This work, while providing an analysis of organization of genes into functional societies, can potentially be useful in assessing the accuracy of contextual gene annotation based on such interaction networks.
A Simple Mathematical Model of Adaptation to High Osmolarity in	Yeast
Authors: Gennemark Peter , Nordlander Bodil , Hohmann Stefan , Wedelin Dag
Published: January 2025

We present a simple ordinary differential equation (ODE) model of the adaptive response to an osmotic shock in the yeast Saccharomyces cerevisiae. The model consists of two main components. First, a biophysical model describing how the cell volume and the turgor pressure are affected by varying extra-cellular osmolarity. The second component describes how the cell controls the biophysical system in order to keep turgor pressure, or equivalently volume, constant. This is done by adjusting the glycerol production and the glycerol outflow from the cell. The complete model consists of 4 ODEs, 3 algebraic equations and 10 parameters. The parameters are constrained from various literature sources and estimated from new and previously published absolute time series data on intra-cellular and total glycerol. The qualitative behaviour of the model has been successfully tested on data from other genetically modified strains as well as data for different input signals. Compared to a previous detailed model of osmoregulation, the main strength of our model is its lower complexity, contributing to a better understanding of osmoregulation by focusing on relationships which are obscured in the more detailed model. Besides, the low complexity makes it possible to obtain more reliable parameter estimates.
Prophage Finder: A Prophage Loci Prediction Tool for Prokaryotic	Genome Sequences
Authors: Bose M. , Barber Robert D.
Published: January 2025

Prophage loci often remain under-annotated or even unrecognized in prokaryotic genome sequencing projects. A PHP application, Prophage Finder, has been developed and implemented to predict prophage loci, based upon clusters of phage-related gene products encoded within DNA sequences. This application provides results detailing several facets of these clusters to facilitate rapid prediction and analysis of prophage sequences. Prophage Finder was tested using previously annotated prokaryotic genomic sequences with manually curated prophage loci as benchmarks. Additional analyses from Prophage Finder searches of several draft prokaryotic genome sequences are available through the Web site (http://bioinformatics.uwp.edu/~phage/DOEResults.php) to illustrate the potential of this application.
SMS: Sequence, Motif and Structure – A Database on the Structural	Rigidity of Peptide Fragments in Non-Redundant Proteins
Authors: Balamurugan Bhagavathimuthu , Roshan M.N.A. Mohd. , Michael Daliah , Ambaree Majumder , Divya Subramanyam , Keerthana Hanumanthagowda , Seemanthini Mahadev , Sekar Kanagaraj
Published: January 2025

Structure prediction methods aim to identify the relationship between the amino acid sequence of an unknown protein and information comprised in databases of known protein structures. Towards this end, we created a database by combining the amino acid sequences and the corresponding three-dimensional atomic coordinates for all the 25% non-redundant protein chains available in the Protein Data Bank. It contains information about the peptide fragments that are 5 to 10 residues long. In addition, options are provided for the users to visualize the individual motifs and the superposed fragments in the client machine. Further, useful functionalities are provided to look for similar sequence motifs in all the sequence databases like PDB, 90% non-redundant protein chains, Genome database, PIR and Swiss-Prot. The database is being updated at regular intervals and the same can be accessed over the World Wide Web interface at the following URL: http://pranag.physics.iisc.ernet.in/sms/.
First Exons and Introns – A Survey of GC Content and Gene	Structure in the Human Genome
Authors: Kalari Krishna R. , Casavant Melanie , Bair Thomas B. , Keen Henry L. , Comeron Josep M. , Casavant Thomas L. , Scheetz Todd E.
Published: January 2025

Most transcriptional regulatory elements are located in non-coding DNA. In particular, some first introns play a vital role in transcriptional control and splicing. The length and GC-content of first exons and introns in complex organisms suggests that these structural units are likely to be important functional elements in large genomes. Hence, in this paper we perform a systematic comparison of exon-intron structure and GC content on all known genes in the human genome. Our in-silico analysis found that the GC content of introns and exons varies significantly depending on their length. On average, the first intron of a gene is significantly longer than other introns in the same gene. Our results also show that first introns and exons are more GC rich than last and internal. This study provides insight into the structure of eukaryotic genes. These results confirm and expand the previously identified regulatory potential of first exons and introns.
RANDNA: A Random DNA Sequence Generator
Authors: Piva Francesco , Principato Giovanni
Published: January 2025

Monte Carlo simulations are useful to verify the significance of data. Genomic regularities, such as the nucleotide correlations or the not uniform distribution of the motifs throughout genomic or mature mRNA sequences, exist and their significance can be checked by means of the Monte Carlo test. The test needs good quality random sequences in order to work, moreover they should have the same nucleotide distribution as the sequences in which the regularities have been found. Random DNA sequences are also useful to estimate the background score of an alignment, that is a threshold below which the resulting score is merely due to chance. We have developed RANDNA, a free software which allows to produce random DNA or RNA sequences setting both their length and the percentage of nucleotide composition. Sequences having the same nucleotide distribution of exonic, intronic or intergenic sequences can be generated. Its graphic interface makes it possible to easily set the parameters that characterize the sequences being produced and saved in a text format file. The pseudo-random number generator function of Borland Delphi 6 is used, since it guarantees a good randomness, a long cycle length and a high speed.

We have checked the quality of sequences generated by the software, by means of well-known tests, both by themselves and versus genuine random sequences. We show the good quality of the generated sequences. The software, complete with examples and documentation, is freely available to users from: http://www.introni.it/en/software.
In Silico Analysis of	Burkholderia pseudomallei Genome Sequence	for Potential Drug Targets
Authors: Chong Chan-Eng , Lim Boon-San , Nathan Sheila , Mohamed Rahmah
Published: January 2025

Recent advances in DNA sequencing technology have enabled elucidation of whole genome information from a plethora of organisms. In parallel with this technology, various bioinformatics tools have driven the comparative analysis of the genome sequences between species and within isolates. While drawing meaningful conclusions from a large amount of raw material, computer-aided identification of suitable targets for further experimental analysis and characterization, has also led to the prediction of non-human homologous essential genes in bacteria as promising candidates for novel drug discovery. Here, we present a comparative genomic analysis to identify essential genes in Burkholderia pseudomallei. Our in silico prediction has identified 312 essential genes which could also be potential drug candidates. These genes encode essential proteins to support the survival of B. pseudomallei including outer-inner membrane and surface structures, regulators, proteins involved in pathogenenicity, adaptation, chaperones as well as degradation of small and macromolecules, energy metabolism, information transfer, central/intermediate/miscellaneous metabolism pathways and some conserved hypothetical proteins of unknown function. Therefore, our in silico approach has enabled rapid screening and identification of potential drug targets for further characterization in the laboratory.
Enhanced Structure Prediction of Gene Products Containing Class	III Adenylyl Cyclase Domains
Authors: Reddy Chandrashekar , Manonmani Arunachalam , Babu Meenakshi , Sowdhamini Ramanathan
Published: January 2025

Domain finding algorithms are useful to understand overall domain architecture and to propose biological function to gene products. Automated methods of applying these tools to large-scale genome studies often employ stringent thresholds to recognize sequence domains. The realization of additional domains can be tedious involving manual intervention but can lead to better understanding of overall biological function. We propose a multi-step approach for the further examination of unassigned linker regions that exploits properties such as the conservation of domain architectures of homologous proteins to propose connections. Improved structure prediction is possible starting from initial domain architectures, obtained from simple 'domain finding' techniques, by concentrating on connecting unassigned regions. 254 unassigned regions have been examined in 114 gene products that potentially contain at least one class III adenylyl cyclase domain for a pilot study. Reliable structure prediction was possible for nearly 80% of unassigned regions. New connections were recognized that assign putative structure and function to these regions by indirect searches (26%. Several others (34%) could be associated with three-dimensional models that might pertain to novel folds and new functions with enough structural content and evolutionary conservation. The presence of additional domains will provide further clues to the overall function of the gene products and their recruitment in particular biochemical pathways.
Engineering Life through Synthetic Biology
Authors: Chopra Paras , Kamma Akhil
Published: January 2025

Synthetic Biology is a field involving synthesis of novel biological systems which are not generally found in nature. It has brought a new paradigm in science as it has enabled scientists to create life from the scratch, hence helping better understand the principles of biology. The viability of living organisms that use unnatural molecules is also being explored. Unconventional projects such as DNA playing tic-tac-toe, bacterial photographic film, etc. are taking biology to its extremes. The field holds a promise for mass production of cheap drugs and programming bacteria to seek-and-destroy tumors in the body. However, the complexity of biological systems make the field a challenging one. In addition to this, there are other major technical and ethical challenges which need to be addressed before the field realizes its true potential.
Protein Subcellular Localization Prediction Using a Hybrid of	Similarity Search and Error-Correcting Output Code Techniques That Produces	Interpretable Results
Authors: Doderer Mark , Yoon Kihoon , Salinas John , Kwek Stephen
Published: January 2025

In silico prediction of protein subcellular localization based on amino acid sequence can reveal valuable information about the protein's innate roles in the cell. Unfortunately, such prediction is made difficult because of complex protein sorting signals. Some prediction methods are based on searching for similar proteins with known localization, assuming that known homologs exist. However, it may not perform well on proteins with no known homolog. In contrast, machine learning-based approaches attempt to infer a predictive model that describes the protein sorting signals. Alas, in doing so, it does not take advantage of known homologs (if they exist) by doing a simple "table lookup". Here, we capture the best of both worlds by combining both approaches.

On a dataset with 12 locations, similarity-based and machine learning independently achieve an accuracy of 83.8% and 72.6%, respectively. Our hybrid approach yields an improved accuracy of 85.9%. We compared our method with three other methods' published results. For two of the methods, we used their published datasets for comparison. For the third we used the 12 location dataset. The Error Correcting Output Code algorithm was used to construct our predictive model. This algorithm gives attention to all the classes regardless of number of instances and led to high accuracy among each of the classes and a high prediction rate overall.

We also illustrated how the machine learning classifier we use, built over a meaningful set of features can produce interpretable rules that may provide valuable insights into complex protein sorting mechanisms.
Theoretical Study of Escherichia Coli Peptide Deformylase	Inhibition by Several Drugs
Authors: Chikhi Abdelouahab , Bensegueni Abderrahmane , Boulahrouf Abderrahmane , Bencharif Mustapha
Published: January 2025

Because peptide deformylase (PDF) is essential for the initiation of translation in eubacteria but not in eukaryotes, it is a potentially interesting target for antibiotics. Computer simulation using docking software can be used to model protein-ligand interactions, and in this brief report we describe its use in optimizing the design in PDF-directed inhibitors.

PDF was used as target for a set of five inhibitors with substantial structural differences. Docking results show that the compound 1BB2 (actinonin) binds with high affinity to the enzyme and produces the most stable complex, forming nine hydrogen bonds with the enzyme active site. Its binding energy is ΔG=−31.880 kJ/mol. The modeling study shows that when the methyl group of 1BB2 is replaced with an amine group, the binding energy is increased to −35.316 kJ/mole. This enhancement is more marked (ΔG=−41.141 kJ/mol) when the propyl group and the five-membered ring of 1BB2 are replaced by an amide group and a phenyl ring, respectively.

We describe an attempt to design better antibiotics on the basis of a computer-aided simulation of the interaction between a drug and its target molecule.
T-iDT: Tool for Identification of Drug Target in Bacteria and	Validation by Mycobacterium Tuberculosis
Authors: Singh Nitesh Kumar , Selvam S. Mahalaxmi , Chakravarthy Paulsharma
Published: January 2025

With the completion of the Human Genome Project in 2003, many new projects to sequence bacterial genomes were started and soon many complete bacterial genome sequences were available. The sequenced genomes of pathogenic bacteria provide useful information for understanding host-pathogen interactions. These data prove to be a new weapon in fighting against pathogenic bacteria by providing information about potential drug targets. But the limitation of computational tools for finding potential drug targets has hindered the process and further experimental analysis. There are many in silico approaches proposed for finding drug targets but only few have been automated. One such approach finds essential genes in bacterial genomes with no human homologue and predicts these as potential drug targets. The same approach is used in our tool. T-iDT, a tool for the identification of drug targets, finds essential genes by comparing a bacterial gene set against DEG (Database of Essential Genes) and excludes homologue genes by comparing against a human protein database. The tool predicts both the set of essential genes as well as potential target genes for the given genome. The tool was tested with Mycobacterium tuberculosis and results were validated. With default parameters, the tool predicted 236 essential genes and 52 genes to encode potential drug targets. A pathway-based approach was used to validate these potential drug target genes. The pathway in which the products of these genes are involved was determined. Our analysis shows that almost all these pathways are very essential for the bacterial survival and hence these genes encode possible drug targets. Our tool provides a fast method for finding possible drug targets in bacterial genomes with varying stringency level. The tool will be helpful in finding possible drug targets in various pathogenic organisms and can be used for further analysis in novel therapeutic drug development. The tool can be downloaded from http://www.milser.co.in/research.htm and http://www.srmbioinformatics.edu.in/forum.htm.
Using Grid Technology for Computationally Intensive Applied	Bioinformatics Analyses
Authors: Andrade Jorge , Berglund Lisa , Uhlén Mathias , Odeberg Jacob
Published: January 2025

For several applications and algorithms used in applied bioinformatics, a bottle neck in terms of computational time may arise when scaled up to facilitate analyses of large datasets and databases. Re-codification, algorithm modification or sacrifices in sensitivity and accuracy may be necessary to accommodate for limited computational capacity of single work stations. Grid computing offers an alternative model for solving massive computational problems by parallel execution of existing algorithms and software implementations. We present the implementation of a Grid-aware model for solving computationally intensive bioinformatic analyses exemplified by a blastp sliding window algorithm for whole proteome sequence similarity analysis, and evaluate the performance in comparison with a local cluster and a single workstation. Our strategy involves temporary installations of the BLAST executable and databases on remote nodes at submission, accommodating for dynamic Grid environments as it avoids the need of predefined runtime environments (preinstalled software and databases at specific Grid-nodes). Importantly, the implementation is generic where the BLAST executable can be replaced by other software tools to facilitate analyses suitable for parallelisation. This model should be of general interest in applied bioinformatics. Scripts and procedures are freely available from the authors.