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Octopus

Octopuses are highly intelligent marine invertebrates belonging to the class Cephalopoda.
These fascinating creatures are known for their remarkable camouflage abilities, complex nervous systems, and unique anatomy, including eight flexible arms.
Octopuses exhibit advanced problem-solving skills and social behaviors, making them a captivating subject of scientific study.
Researchers utilize PubCompare.ai's AI-powered platform to unlock new insights and reproducibility in Octopus research, identifiying optimal protocols, products and procedures to advance their studies with confidence.
Experiance the future of scientific reproducibility today.

Most cited protocols related to «Octopus»

1
Consensus Transmembrane Topology Prediction
Cited 76 times
The CCTOP method has three main steps: removing cleavable parts of a target sequence, TMP filtering and topology prediction. Signal peptide segments are often mistaken with TMHs by transmembrane topology prediction algorithms, therefore a preceding analysis of these segments was applied. CCTOP uses SignalP 4.0 (34 (link)) to cleave signal peptides; however, this step can be ignored, if a homologous protein in the TOPDB database (35 (link),36 (link)) has contradictory evidence.
After removing cleavable segments the next step is to distinguish transmembrane and globular proteins. For this task a simple voting system is applied on the results of Phobius (37 (link)), Scampi-single (38 (link)) and TMHMM (2 (link),39 (link)) algorithms. If any two of these methods predict transmembrane segment(s), the protein is classified as TMP.
A variety of methods was taken into account for the consensus topology prediction, regarding both the training set and the utilized algorithm. Ten methods were selected based on their availability and performance on different benchmark sets: HMMTOP (28 (link),40 (link)), MemBrain (41 (link)), MEMSAT-SVM (42 ), Octopus (43 (link)), Philius (44 (link)), Phobius (37 (link)), Pro- and Prodiv-TMHMM (45 (link)), Scampi-MSA (38 (link)) and TMHMM (2 (link),39 (link)). The prediction results of these methods are used as constraints in the same hidden Markov model that was used by HMMTOP but with different weights. The weights depend on the accuracy of each method, measured on a benchmark set collected for the Human Transmembrane Proteome database (3 ). To further improve the prediction accuracy for each query, its homologous structures from PDBTM (4 (link)–6 (link)), experiments of homologous sequences from TOPDB (35 (link),36 (link)) and conservatively localized domains and motifs from TOPDOM (46 (link)) recognized in the query sequence are collected automatically and all these information is incorporated into a probabilistic framework provided by a hidden Markov model as described in Bagos et al. (47 ). A formalized and more detailed description of the algorithm is available in our earlier paper (3 ) and on the home page of the CCTOP server.
Dobson L., Reményi I, & Tusnády G.E. (2015). CCTOP: a Consensus Constrained TOPology prediction web server. Nucleic Acids Research, 43(Web Server issue), W408-W412.
Publication 2015
Eye Homologous Sequences Homo sapiens Octopus Proteins Proteome Signal Peptides
2
Comprehensive Protein Dataset for Model Evaluation
Cited 33 times
We used the Phobius dataset [9] (link) during model development. This dataset consists of four non-overlapping subsets of 1087 globular (G) proteins, 1275 globular proteins with signal peptides (SP+G), 247 transmembrane (TM) proteins and 45 transmembrane proteins with signal peptides (SP+TM). The maximum homology among the 247 TM proteins is 80%, and the maximum homology among the 45 SP+TM proteins is 35%. The same cross-validation folds and the same labels that were used to train and test Phobius were also used in this work.
Two additional datasets were obtained and used in the final testing and evaluation of the model: the SCAMPI dataset [27] (link) of 124 transmembrane proteins (http://octopus.cbr.su.se/index.php?about=download) and the SignalP 3.0 [28] (link) training dataset. The labels in the SCAMPI dataset include re-entrant regions which do not completely span the membrane. These were removed and relabeled as inside or outside because Philius does not currently model those types of segments. The maximum homology among these 124 proteins is 40%. Based on homology between these and the original Phobius TM proteins, this set was divided into one set of 77 proteins that does not overlap the Phobius dataset (maximum homology 80%), and one set of 47 proteins that does. For the purposes of training and testing Philius we only used the signal peptide portion of the SignalP dataset, combining the eukaryotic and bacterial proteins into a single set of 1728 proteins. Truncated versions of these proteins were used in training because the labels covered only the signal peptide and cleavage-site of each protein.
Reynolds S.M., Käll L., Riffle M.E., Bilmes J.A, & Noble W.S. (2008). Transmembrane Topology and Signal Peptide Prediction Using Dynamic Bayesian Networks. PLoS Computational Biology, 4(11), e1000213.
Publication 2008
Bacterial Proteins Eukaryotic Cells Eye GTP-Binding Proteins Integral Membrane Proteins Octopus Proteins Proteolysis SET protein, human Signal Peptides Tissue, Membrane
3
Factors Influencing Visual Field in Glaucoma
Cited 23 times
Data were from 394 eyes of 197 patients aged 65 years or older who were seen for glaucoma treatment or were evaluated for a possible diagnosis of glaucoma in the Glaucoma Consultation Service of the Massachusetts Eye and Ear Infirmary. All patients had perimetry via an Octopus perimeter (Haag-Streit AG, Koeniz, Switzerland[AU: confirm?]) in each eye.7 (link)–8 (link) The percentage of normal visual field in an eye was calculated as the average threshold in the central 30° standardized by the normal value for a 65-year-old person. Distance visual acuity was assessed with the use of spectacles with and without pinhole, and the better of the two measures was taken as the Snellen visual acuity in an eye. Visual acuity was then transformed to a measure of percent impairment. Other measures assessed at the glaucoma examination included lens status in each eye and history of systemic hypertension. We are interested in determining the factors associated with visual field data, including person-specific factors (age, sex, and hypertension status) and eye-specific factors (lens status and visual acuity).
Ying G.S., Maguire M.G., Glynn R, & Rosner B. (2017). Tutorial on Biostatistics: Linear Regression Analysis of Continuous Correlated Eye Data. Ophthalmic epidemiology, 24(2), 130-140.
Publication 2017
Antiglaucoma Agents Diagnosis Eyeglasses Glaucoma Hepatitis A Antigens High Blood Pressures Lens, Crystalline Octopus Patients Perimetry Vision Visual Acuity
4
Automated Membrane Protein Simulations
Cited 21 times
The initial CGSA simulation setup is performed using the MemProtMD pipeline (34 (link)). In brief, integral membrane proteins are identified from the PDB based on an Octopus prediction of surface-assessible α-helical TM domains (38 (link)). Potential β-barrel membrane proteins are identified based on the number, length, accessibility and hydrophobicity of their β-strands. Where available, the biological unit in the PDB is prepared for the oligomeric state of the simulated protein. In all instances non-protein atoms are removed from the PDB entry prior to simulation. MD simulations are performed using GROMACS 5.1.4 (39 ) and the MARTINI 2.2 forcefield (40 (link)). Completed simulations are then converted to atomistic representation using CG2AT (30 (link)). Analysis of completed simulations is performed using Python, MDAnalysis (41 (link)) and our in house mpm-tools, which includes bindings for MUSCLE (42 (link)) and a python adaptor for VMD (43 (link)), used to render static images. Two dimensional visualizations of data are performed using D3.js. Three dimensional protein visualization uses PV. The database is stored using MongoDB. The web server uses NodeJS and Express to serve a frontend application built on ReactJS and Redux. Server application deployment is performed using Docker Compose.
Newport T.D., Sansom M.S, & Stansfeld P.J. (2018). The MemProtMD database: a resource for membrane-embedded protein structures and their lipid interactions. Nucleic Acids Research, 47(Database issue), D390-D397.
Publication 2018
Biopharmaceuticals Helix (Snails) Integral Membrane Proteins Membrane Proteins Muscle Tissue Octopus Proteins Python Redux
5
Improved TOPCONS Protein Topology Prediction
Cited 21 times
The core algorithm of TOPCONS remains the same as the earlier implementation, with the addition of a signal peptide module (see Figure 1). The topology predictions from the five sub-methods used (OCTOPUS, Philius, PolyPhobius, SCAMPI and SPOCTOPUS) are combined into a topology profile, where each residue is represented by four values, corresponding to the fraction of methods that predict that particular residue to belong to a signal peptide (S), a membrane region (M) or the membrane-inside and outside (i and o, respectively). A dynamic programming algorithm, represented as a Hidden Markov Model, that has an alphabet consisting of the characters ‘S’, ‘M’, ‘i’ and ‘o’ processes the resulting profile. The final topology corresponds to the highest scoring state path through this model using a Viterbi-like algorithm. In each state, the emission score for the structural category modeled by that state (S, i, o or M) is equal to 1.0 and for all other structural categories it equals to 0.0. All transition probabilities are equal to 1.0. Thus, the final prediction equals to the state path with the highest geometric mean score with respect to the topology profile and the grammar of the model, and no training of the model is necessary. In addition, the biological hydrophobicity scale (38 (link)) is used to predict the free energy of membrane insertion for a window of 21 amino acids centered on each position in the sequence.
Tsirigos K.D., Peters C., Shu N., Käll L, & Elofsson A. (2015). The TOPCONS web server for consensus prediction of membrane protein topology and signal peptides. Nucleic Acids Research, 43(Web Server issue), W401-W407.
Publication 2015
Amino Acids Biopharmaceuticals Character Octopus Signal Peptides Tissue, Membrane

Most recents protocols related to «Octopus»

1
Gene prediction and annotation for C. bisecta
Ab initio, homology-based and gene expression evidence were combined to predict protein-coding genes in the genome of C. bisecta. Augustus v3.1 was first employed on repeat-masked genome for ab initio gene prediction [106 (link)]. For the homology-based annotation, gene sets from 10 molluscan species (Archivesica marissinica, Biomphalaria glabrata, Crassostrea gigas, Gigantidas platifrons, Lottia gigantea, Lutraria rhynchaena, Modiolus philippinarum, Octopus bimaculoides, Pinctada fucata, and P. canaliculate) were used. These homologous protein sequences were first aligned onto the genome of C. bisecta using Blast v2.2.26 with an e-value cut-off of 1 × 10−5 [107 (link)], and then we linked the alignment hits to candidate gene loci by GenBlastA [108 (link)]. Secondly, genomic sequences of candidate gene regions together with their 2-kb flanking sequences were extracted and used GeneWise v2.2.0 to determine gene models [109 (link)]. Moreover, Stringtie v 1.3.4 was employed to generated gene annotation files on RNA-Seq alignments generated by HISAT v2.1.0 of different tissues (adductor muscle, mantle, foot, and gill) [110 (link), 111 (link)]. Then these files were merged together to predict candidate coding regions open reading frames (ORFs) using Transdecoder v5.5.0 and were aligned to genomes to obtain a gene annotation file with transcript evidence. Finally, these three evidences were integrated using EVM v1.1.1 to obtain a final version of protein-coding genes [112 (link)], and their function were annotated by searching against the following public databases: Swiss-Prot v201709, KEGG v87.0, InterPro v55.0, and TrEMBL v201709. The other 7 species used in gene family analysis were functionally annotated in the same way.
Guo Y., Meng L., Wang M., Zhong Z., Li D., Zhang Y., Li H., Zhang H., Seim I., Li Y., Jiang A., Ji Q., Su X., Chen J., Fan G., Li C, & Liu S. (2023). Hologenome analysis reveals independent evolution to chemosymbiosis by deep-sea bivalves. BMC Biology, 21, 51.
Publication 2023
Amino Acid Sequence Australorbis glabratus Crassostrea gigas FCER2 protein, human Foot Gene Annotation Gene Expression Gene Products, Protein Genes Genes, vif Genome Gills Homologous Sequences Muscle Tissue Octopus Open Reading Frames Pinctada Protein C Proteins RNA-Seq Tissues
2
Lophotrochozoan Phylogenomic Analysis
Twenty-four well-assembled lophotrochozoan genomes were selected for phylogenetic analysis, include one annelid (Helobdella robusta) as outgroup, 21 bivalves (Archivesica marissinica, Argopecten concentricus, Argopecten irradians, Conchocele bisecta, Crassostrea gigas, Crassostrea virginica, Cyclina sinensis, Gigantidas platifrons, Lutraria rhynchaena, Mactra quadrangularis, Mercenaria mercenaria, Mizuhopecten yessoensis, Modiolus philippinarum, Mytilus coruscus, Pecten maximus, Pinctada fucata, Pinctada imbricata, Ruditapes philippinarum, Saccostrea glomerata, Scapharca broughtonii, Sinonovacula constricta), 5 gastropods (Aplysia californica, Chrysomallon squamiferum, Lottia gigantea, Haliotis rufescens, Pomacea canaliculata), and 2 cephalopods (Octopus bimaculoides and Octopus vulgaris) [22 (link), 26 (link), 52 (link), 113 (link)–132 ]. SonicParanoid v1.3.0 was used to define gene family clusters among different species [133 (link)]. The amino acid sequences of one-to-one single-copy orthologous genes were used to reconstruct their phylogenetic topology. The protein sequences were aligned using MAFFT v7.407 under default settings [134 (link)], and then were concatenated for phylogenetic analysis using a maximum-likelihood method implemented in IQ-TREE v 2.0.6 with the “-m MFP” parameter was applied to each protein partition [135 (link)]. To estimate divergence times, the rooted maximum-likelihood tree, along with a concatenated fourfold degenerate site sequence extracted from single-copy CDS (coding sequence), was used as the input of MCMCtree software implemented in PAML v4.8 [136 (link)]. For calibration, nine nodes were constrained by either fossil records obtained from website of TimeTree.
Guo Y., Meng L., Wang M., Zhong Z., Li D., Zhang Y., Li H., Zhang H., Seim I., Li Y., Jiang A., Ji Q., Su X., Chen J., Fan G., Li C, & Liu S. (2023). Hologenome analysis reveals independent evolution to chemosymbiosis by deep-sea bivalves. BMC Biology, 21, 51.
Publication 2023
Amino Acid Sequence Aplysia Bivalves Cephalopoda Crassostrea gigas Crassostrea virginica Gastropods Genes Genome Mercenaria Mizuhopecten yessoensis Mytilus Octopus Open Reading Frames Pecten maximus Pinctada Proteins Scapharca Trees
3
Comparative RNA Editing Across Species
To increase the phylogenetic coverage of the investigated species, we collected the matching DNA-seq and strand-specific RNA-seq data from the nematode Caenorhabditis elegans (pooled whole organisms collected from three larval stages and two adult stages),13 (link) the leaf-cutting ant Acromyrmex echinatior (three pooled head samples of the small worker caste collected from three colonies, respectively),34 (link) the octopus Octopus bimaculoides (four neural tissue samples including faxial nerve cord, optic lobe, subesophageal ganglia and supraesophageal ganglia)43 (link) and human (three brain samples from three male adults, respectively).10 (link) The NCBI SRA accession numbers and statistics of the downloaded sequencing data were presented in Table S1. RNA-editing sites in each of the four species were identified using the same procedure (step i to v) as described above.
Zhang P., Zhu Y., Guo Q., Li J., Zhan X., Yu H., Xie N., Tan H., Lundholm N., Garcia-Cuetos L., Martin M.D., Subirats M.A., Su Y.H., Ruiz-Trillo I., Martindale M.Q., Yu J.K., Gilbert M.T., Zhang G, & Li Q. (2023). On the origin and evolution of RNA editing in metazoans. Cell Reports, 42(2), 112112.
Publication 2023
Adult Brain Caenorhabditis elegans Cone-Rod Dystrophy 2 Eye Ganglia Head Homo sapiens Larva Males Nematoda Nerve Tissue Nervousness Octopus Plant Leaves RNA-Seq Workers
4
Comparative Analysis of GO Enrichment in Recoded Genes
GO annotations for the protein-coding genes were downloaded from Ensembl (Caenorhabditis elegans, Ciona savignyi, Danio rerio and Homo sapiens) or Ensembl Metazoa (Mnemiopsis leidyi, Amphimedon queenslandica, Drosophila melanogaster, Drosophila simulans, Crassostrea gigas, Octopus bimaculoides, Nematostella vectensis and Strongylocentrotus purpuratus) via the BioMart function. For Hydra vulgaris, Aplysia californica, Acromyrmex echinatior, Ptychodera flava and Branchiostoma belcheri that do not have publicly available GO annotations, we first aligned all the proteins of these species to the UniProt database (release-2019_04) using BLASTP93 (link) with parameters -F F -e 1e-5. Then the best hit of each query gene was retained based on its BLASTP bit score, and the GO annotations of this best hit was assigned to the query gene.
GO enrichment analysis was conducted for genes with at least one putatively beneficial recoding site as defined above. Two-sided Fisher’s exact tests were employed to examine whether the recoded genes of a species was enriched in a specific GO term in relation to background genes, by comparing the number of recoded genes annotated to this GO term, the number of recoded genes not annotated to this GO term, the number of background genes (i.e. the protein-coding genes with RPKM >1 in at least one sample after excluding the recoded genes in the species) annotated to this GO term, and the number of background genes not annotated to this GO term. p-values were adjusted for multiple testing by applying FDR,109 (link) and the GO terms with adjusted p-values <0.05 in at least three species (Note: GO terms shared by D. melanogaster and D. simulans were only counted once here) were considered as the functional categories preferred by recoding editing in metazoans (Figure 5D).
Zhang P., Zhu Y., Guo Q., Li J., Zhan X., Yu H., Xie N., Tan H., Lundholm N., Garcia-Cuetos L., Martin M.D., Subirats M.A., Su Y.H., Ruiz-Trillo I., Martindale M.Q., Yu J.K., Gilbert M.T., Zhang G, & Li Q. (2023). On the origin and evolution of RNA editing in metazoans. Cell Reports, 42(2), 112112.
Publication 2023
Aplysia Branchiostoma belcheri Caenorhabditis elegans Ciona savignyi Crassostrea gigas Drosophila melanogaster Drosophila simulans Gene Products, Protein Genes Genetic Background Homo sapiens Hydra Metazoa Mnemiopsis Octopus Protein Annotation Proteins Strongylocentrotus purpuratus Zebrafish
5
Robotic-Assisted Minimally Invasive Direct Coronary Artery Bypass
The RA-MIDCAB procedure was performed in a standardized fashion by a dedicated team in each institution. In each institution, there was a single surgeon who performed the RA-MIDCAB procedures. Standard surgical procedures of each institution were followed. In summary, patients were placed in the supine position with a 10 cm soft roll or balloon under the chest between the scapulae and the left arm, allowing the left shoulder to be deflected posteriorly. The camera port was placed in the fourth/fifth intercostal space (ICS) medial to the anterior axillary line. Working ports were typically placed in the second/third and the sixth/seventh ICS medial to the anterior axillary line. Preferably, the distance between the ports was at least 10 cm to avoid instrument collisions and to maximize the working area. Once adequate port placement was achieved, LITA harvesting occurred. Single-lung ventilation or a bronchial blockage was used to deflate the left lung and therefore optimize the intrathoracic working space. In addition, CO2 insufflation from 5 to 10 mm Hg was exploited, and a 0° or 30° up-scope was used in most cases. The LITA was taken down with care using a combination of blunt dissection and electrocautery in either a skeletonized or pedicled fashion. Once the LITA was harvested, a pericardiectomy was performed robotically, and the target coronary vessel, namely, the LAD, was identified. Appropriate heparinization was achieved if the activated clotting time was >300 s. With the robotic camera still in place, a needle was used to identify the optimal intercostal space for the small thoracotomy, usually 4 to 7 cm long. After robot undocking, the minithoracotomy was made and a soft tissue retractor placed. The endoscopic Octopus Nuvo (Medtronic, Dublin, Ireland) or Acrobat-i Stabilizer (MAQUET, Getinge, Göteborg, Sweden) off-pump stabilizer was inserted via a previous port site or direct through the minithoracotomy and was used to stabilize the target vessel while off-pump coronary anastomosis was performed in the usual fashion. If a conversion to sternotomy was required, a conventional on-pump or off-pump CABG was performed.
de Jong A.R., Gianoli M., Namba H.F., Roefs M.M., Singh S., Segers P., Jacob K.A, & Suyker W.J. (2023). A Nationwide Study of Clinical Outcomes After Robot-Assisted Coronary Artery Bypass Surgery and Hybrid Revascularization in the Netherlands. Innovations (Philadelphia, Pa.), 18(1), 73-79.
Publication 2023
Axilla Blood Vessel Bronchi Chest Coronary Artery Bypass Surgery Coronary Vessels Dissection Electrocoagulation Endoscopy Heart Insufflation Lung Needles Nuvo Octopus One-Lung Ventilation Operative Surgical Procedures Patients Pericardiectomy Scapula Shoulder Sternotomy Surgeons Surgical Anastomoses Thoracotomy Tissues

Top products related to «Octopus»

1
Octopus 900 perimeter by Haag-Streit
Sourced in Switzerland
The Octopus 900 perimeter is a diagnostic instrument used for visual field testing. It is designed to assess and analyze the visual field of a patient's eyes.
2
Octopus 900 by Haag-Streit
Sourced in Switzerland, Germany
The Octopus 900 is a comprehensive visual field analyzer designed for comprehensive perimetric examinations. It features a high-resolution, large-scale perimetric bowl that provides a wide visual field coverage. The device uses advanced technology to accurately measure and record the patient's visual field, enabling detailed analysis and assessment of visual function.
3
Scmos camera by Oxford Instruments
Sourced in United Kingdom, Germany
The sCMOS camera from Oxford Instruments is a scientific-grade imaging device that utilizes a scientific Complementary Metal-Oxide-Semiconductor (sCMOS) sensor. The sCMOS camera offers high-resolution, low-noise, and high-speed image capture for various scientific and industrial applications.
4
Octopus by Haag-Streit
Sourced in Switzerland
The Octopus is a versatile lab equipment designed to facilitate various laboratory tasks. It features multiple connected arms that can hold and manipulate a variety of tools and samples simultaneously. The core function of the Octopus is to provide a flexible and efficient workspace for researchers and technicians working in a laboratory setting.
5
Octopus by Medtronic
Sourced in United States
The Octopus is a high-performance lab equipment designed for a variety of applications. It features multiple channels for simultaneous monitoring and data collection. The core function of the Octopus is to provide advanced measurement and analysis capabilities to support research and laboratory workflows.
6
Octopus perimeter 101 by Haag-Streit
Sourced in Switzerland
The OCTOPUS® Perimeter 101 is a compact and fully automated perimeter device designed for visual field testing. It features a high-resolution touchscreen display, a wide testing range, and advanced software for comprehensive analysis of visual field data.
7
Spectralis oct by Heidelberg Engineering
Sourced in Germany, United States, United Kingdom, Japan
The Spectralis OCT is a high-resolution optical coherence tomography (OCT) imaging system designed for clinical use. It provides detailed, cross-sectional images of the eye's internal structures, enabling healthcare professionals to diagnose and monitor a variety of ocular conditions.
8
Spectralis by Heidelberg Engineering
Sourced in Germany, United States, United Kingdom, Japan, Switzerland, Ireland
The Spectralis is an optical coherence tomography (OCT) imaging device developed by Heidelberg Engineering. It captures high-resolution, cross-sectional images of the retina and optic nerve using near-infrared light. The Spectralis provides detailed structural information about the eye, which can aid in the diagnosis and management of various eye conditions.
9
Octopus tissue stabilizer by Medtronic
Sourced in United States
The Octopus tissue stabilizer is a medical device designed to stabilize tissue during surgical procedures. It is a handheld instrument that uses specialized suction cups to gently grip and hold the target tissue in a stable position, allowing for precise surgical manipulation and treatment.
10
Octopus 3 by Medtronic
Sourced in United States
The Octopus III is a multi-channel data acquisition system designed for laboratory applications. It features multiple input channels for the simultaneous recording of various signals, such as electrical, mechanical, or physiological data. The Octopus III provides high-quality data acquisition capabilities, enabling researchers and scientists to capture and analyze complex experimental data with precision.

More about "Octopus"

Cephalopods, Cuttlefish, Nautilus, Squid, Marine Invertebrates, Nervous System, Camouflage, Problem-Solving, Social Behavior, Scientific Research, Octopus 900 perimeter, Octopus 900, SCMOS camera, OCTOPUS® Perimeter 101, Spectralis OCT, Spectralis, Octopus tissue stabilizer, Octopus III.
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Explore the fascinating world of these highly intelligent marine creatures, known for their remarkable camouflage, complex nervous systems, and unique anatomy.
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