dataesr/scientific-paragraphs-categorization huggingface dataset:
Furthermore, autosomes are moderately up-regulated. Third, the fold change/ extent of the down-regulation occurs in a range that is consistent with an approximately twofold, DC-like effect (Fig 3A; log 2 FC of -0. 415 assuming a 50:50 male:female population, where males are affected by twofold and females are unaffected; grey bar). Indeed, the majority of the downregulated genes (1,103 of 1,304) are reduced to 25-75% of control levels. We conclude that X-linked perturbations due to defective DC can be reliably scored from such a mixedpopulation experiment. For Anopheles, we first inspected the earlier dataset around 6-7 h after egg laying, and found few gene expression changes in msl-2 KO embryos  (Fig S3C and D). A total of five significantly down-regulated genes (FDR < 0. 05) included msl-2 itself, three transcripts directly adjacent to msl-2, and the orthologue of Dmel mira, an actin/myosin binding protein.
Right: bar plot displaying the relative enrichment of msls and controls (not translated: U6 snRNA; translated: Rps4 mRNA) in the polysomal fractions. The data for all fractions individually is reported in Fig S1F. The barplot represents the mean ± SEM with overlaid data points reflecting one polysome profiling experiment/biological replicate. were affected by at least 75% or more (Tables  S2  and S3  and Fig 3D ). An overall down-regulation of the X chromosome or an up-regulation of autosomes was also not detectable in the Anopheles dataset (Fig  3F  and Table  S1 ). We conclude that loss of MSL2 in Anopheles embryos leads to global changes in gene expression affecting all chromosomes (for functional analyses on MSL2-evoked transcriptome alterations not related to X-chromosome-wide DC see below).
A. gambiae MSL2 regulates conserved developmental genes The aforementioned observations indicate that the MSL complex-H4K16ac pathway is unlikely to mediate chromosome-wide DC in Agam. We were therefore interested in which functions and generegulatory networks MSL2 might be controlling. To this end, we analyzed our RNA-seq dataset for the enrichment of distinctive features among the DE genes. This revealed that DE genes in msl-2 KO embryos tend to be significantly longer than average in the Anopheles genome (e. g. , at the level of coding sequence, transcript length, gene span as well as the number of exons, Figs  6A  and S6B ). Furthermore, we found a significantly higher fraction of Drosophila orthologues in the msl-2 KO DE group than expected (Fisher's test P = 6. 34 × 10 -18 ) indicating that the Anopheles MSL-regulated genes tend to be conserved among Dipterans  (Fig 6B, left panel).
There was no difference between the expected and DE gene groups at the sequence level (% identity of the orthologues) (Fig 6B, right panel). We next analyzed the features of the proteins encoded by msl-2 KO DE genes using the STRING database of known and predicted protein-protein interactions (Fig  6C )  (Szklarczyk et al, 2018). We find that the proteins encoded by the Top400 DE genes (msl-2 KO versus control) display significantly more protein-protein interactions than expected, indicating that they are highly interactive. If the targets regulated by MSL2 tend to frequently engage in proteinprotein interactions and are part of multisubunit complexes, this may explain why their expression levels need to be tightly controlled by chromatin-regulatory pathways such as the H4K16ac-MSL pathway: poorly controlled expression could lead to stoichiometry imbalances, proteotoxicity and aggregation  (Brennan et al, 2019).
Analysis of the functional domains of MSL2 targets with the Pfam database revealed an enrichment of "homeobox domain," which is a well-known module of developmental transcription factors, but also various other domains mediating processes occurring at the cellular surface  (Fig 6D). We also performed Gene Ontology term   analyses  (Fig 6E and F) , where we found misregulated biological processes such as "multicellular organism development," "tissue development," "tissue morphogenesis," or "cell differentiation" and cellular components such as "plasma membrane," "cell periphery," "extracellular space," or "cell junction. " A prominent example in the down-regulated genes group was the A. gambiae HOX cluster  (Fig 6G). HOX genes encode homeodomain-containing transcription factors that provide specificity and positioning information along the anterior-posterior axis and are conserved master regulators for setting up animal body plans  (Gehring et al, 2009).
Whereas our datasets do not allow us to unambiguously distinguish sequence identity in the target Dmel orthologue. The statistical significance was evaluated by comparing the % sequence identity for all orthologues (n = 971) versus expected using a Wilcoxon test. between these two models for Drosophila, our Anopheles dataset does not provide any evidence for skewed expression of an entire chromosome, neither the X nor autosomes. In addition, our ChIPseq profiles show neither evidence of global X chromosome enrichment nor a sexually dimorphic pattern on a gene-by-gene level. Furthermore, H4K16ac does not form the typical X chromosome "territory" in immunofluorescence indicating that the deposition of this mark is not a universal feature for DC in Dipterans. This is reminiscent of another dipteran, Sciara, where mle and H4K16ac appear to play no role in DC  (Ruiz et al, 2000).
Processing of RNA-seq and ChIP-seq datasets For quality control, we used FastQC version: v0. 11. 3. For RNA-seq, pairedend reads were mapped with RNA STAR (Galaxy version 2. 5. 2b-0) to AgamP4_ensembl or dm6_ensembl with default parameters. Mapping statistics are reported in Table  S1. The raw read counts per gene were obtained with featureCounts  (1. 4. 6. p5). This was followed by differential expression analysis with DESeq2, R version 3. 0. 2. DESeq2 normalizes the read counts with a linear model, where counts for genes are modeled using a negative binomial distribution with fitted mean and a gene-specific dispersion parameter (details in  Love et al [2014] ). Table  S1  reports statistical analyses for the Drosophila RNA-seq dataset for both the conventional DESeq2 standard normalization as well as where the data are normalized to the rRNA reads (note that rRNA species are typically present in RNA-seq data despite the polyA enrichment in the kit for mRNA-Seq).
org)andVectorBase(https://www. vectorbase. org/). Protein alignments were created on Clustal Omega (https://www. ebi. ac. uk/Tools/msa/ clustalo/). Results of BLAST searches (BLASTP, 2. 2. 29+) are reported in TableS1. Lists of 1:1 orthologues were obtained via the Biomart tool on VectorBase. Bowtie2 (https://github. com/BenLangmead/bowtie2)(Langmead&Salzberg,2012);deepTools2(https://deeptools. readthedocs. io/en/latest/)(Ramírezetal,2016);Galaxy(https://github. com/bgruening/galaxytools)(Grüningetal,2017);IGV(https://software. broadinstitute. org/software/igv/)(Robinsonetal,2011);R(https://www. r-project. org);DESeq2(http://bioconductor. org/packages/DESeq2/);GoTermanalysis(http://geneontology. org/)(The Gene Ontology Consortium, 2019); REVIGO (http://revigo. irb. hr/r)(Supeketal,2011);STRING(https:// string-db.
Acknowledgements We thank the  Max Planck Institute of Immunobiology and Epigenetics  facilities and the  IMB Microscopy Core Facility  for support. We thank  Marc Bayer  and  Sarah Toscano  for contributing initial analyses to set up the project, as well as  Devon Ryan  and  Gina Renschler  for help with data processing and bioinformatic analyses. We thank  Gina Renschler ,  Maria Shvedunova , and  Agata Kalita  for their input on the manuscript. CI  Keller Valsecchi  was supported by a  Human   Frontier Science Program long-term fellowship  ( 000233/2014-L ). This study was supported by the  German Research Foundation (DFG)  under  Germany's Excellence Strategy  ( CIBSS-EXC-2189-Project ID 390939984 ). Mosquito production and insectarium operation were supported by  Agence Nationale de la Recherche  grant # ANR-11-EQPX-0022.
In this paper, we investigate how an interactive version of the membership function of the Fuzzy Logic Theory can be used to categorize quantitative data. This function is simple and similar to a line chart and provides an explicit mapping of the categorization process. We first review the requirements for such quantitative values partitioning process and provide the mathematical foundations in Fuzzy Logic related to the membership function. We then report on the implementation of the interactive function for several quantitative datasets case studies (e. g. , age, temperature, speed). We expect this interactive function to provide more control over the categorization process, as well as a way to make the categorization process more explicit.
INTRODUCTION When reasoning on quantitative values-like people's age-analysts tend to use categories like YOUNG and OLD. Such a categorization process aims at mimicking the logic of human thoughts and reasoning  (Clifford et al. , 1975). In the situation where such categories are not in the dataset, it is likely they are subjective, from the analyst's head, based on familiarity with the domain or prior knowledge. Such a process raises the following issues: • An explicit mapping of those categories is missing: the mapping function between quantities and categories should be clearly defined. • The mapping properties may vary across analysis sessions and analysts: the mapping should be consistent and may not change. • The transfer between analysts and a user should be possible: by some means of communication like a legend or a visual representation.
Our main contribution is that we design an interactive version of fuzzy membership function as an interactive chart (Fig. 1 ), which is able to help users categorize quantitative values with confidence belonging to categories. We provide an implementation that demonstrates how it supports the categorization of multiple datasets. Our implementation exposes many parameters of the function that can be adjusted to generate new shapes of membership function for fine-grained categorization. The generated categories from this membership function can be assigned names that are then used as category names in the updated dataset. We conclude with an experimental design for further evaluation of this tool to validate its usability. We expect this technique to be not only used as a categoriesgeneration tool but also as an interactive legend  (Riche et al.
Uncertainty Visualization Research on uncertainty visualization also offers some solutions for the presentation of ambiguity while categorization. In this field, works related to uncertainty visualization provide guidance on advanced properties in the data, i. e. incorrectness, incompleteness, and ambiguity  (Dressel and Nori, 2014). Brodlie  (Brodlie et al. , 2012)  reviewed state of the art in uncertainty visualization according to different data, for example, point data, scalar data, multi-field scalar data, and vector data. At the same time, they also concluded the uncertainty visualization in the various dimensional datasets. Skeels proposed a classification of uncertainty  (Skeels et al. , 2010)  for information visualization. (Dong and Hayes, 2012)  designed an interactive tool to help users recognize the situations and comprehend the ambiguity, which is able to evaluate the domain-dependent decision support system (DSS).
Implementation Details This membership function is implemented in Observable, using library D3  (Bostock et al. , )  and is bundled  as a JavaScript ES6 module compliant with modern Web standards. An online prototype 3  is available along with the datasets described in this paper. Additional datasets can be added using a JSON file specification that captures the configurations that a userdefined. The parameters of configurations include the parameters of specific membership function and categories' names are showed as follows: { "title": "Temperature", "attribute": "0", "parameters": [{ "n": "3", "Core": "13. 6", "Support": "27. 2", "names": [ "Cold", "Warm", "Hot" ]}]} Such configuration enables the rapid export and sharing of the parameters, so they can be used in a different tool and can further be analyzed to understand the categorization process of multiple users.
Case Study with Age Dataset A typical age dataset consists of a semi-bounded interval and rounded values, there exists a minimum value but no fixed maximum value. The dataset we used, in this case, is The Simpsons, a popular U. S. TV Series. The dataset includes 24 characters with an age attribute. Age range from 0 to 90. The dataset is shown in Fig. 5  where ages are represented on the x-axis. The y-axis shows the membership degree for every category so that a user can easily check categories and their membership degrees. The table list below of Fig. 5  shows the categories and their properties. Membership values and the range of categories are shown in the table in Fig. 5 (b), which is corresponding to the membership function and has 5 categories. We can see that the membership degrees of category 1 and category 3 are equal to 0.
Case Study with Taxi Speed Dataset We conduct the third case using a taxi speed dataset. The speed data are semi-rounded and continuous values types. Traffic analysts usually are interested in characterizing taxi drivers' characteristics, which is helpful for them to identify driving behaviors. Obviously, speed is a very essential parameter to define categories, as it reflects many characteristics of drivers. The prototype of taxi speed is showed in Fig. 7 (a) and the table list is showed in Fig. 7 (b). In this case, speed is separated into five categories and their main categories are Low, Middle and High. Besides, there are two fuzzy categories with membership degrees less than 1, named Low-Middle and Mid-High. Other categories, more domain-specific, could have been used, e. g. Slow, Fast by editing the label input field in the prototype.
DISCUSSION AND PERSPECTIVES In this paper, we designed an interactive tool to categorize quantities into categories. By using Fuzzy Logic, it enables splitting quantitative values into categories with a degree called membership degree. We are able to present uncertainties with membership degrees to better capture user knowledge and demonstrated its application using three datasets included in an interactive prototype. The summary of case studies is shown in Table  2. The results suggest that, in most situations, users are likely to categorize quantities into 3 -5 categories with particular names for each category. First, naming generated categories is usually based on social basic knowledge, e. g. , the name of age categories, which includes Children, Adult and Old. But when the categories are complicated, the name of categories tend to be Very.
or Super. There is also another naming method, which combines the basic categories, e. g. , the name Mid-High is derived from Middle and High in speed data. Our tool supports an extensive number of categories, up to several dozens. Beyond this number, it may however become difficult to read the categories' names and interact with them. We identified the following limits in our current work. It does not consider the distribution of quantitative values. The trapezoid membership function can not consider the real distribution of the dataset, instead of building a membership function based on the maximum value, minimum value, and the number of categories. The distribution is not considered in this method. Only categorize dataset with clear maximum value and minimum value. Currently, we can only use the maximum value existed in the dataset or dataset with a clear boundary.
For example, in the age dataset, the maximum value is 90, so the maximum value in this prototype is 90, it is totally based on the range of the dataset. Limitation in categorizing quantities with rounded values: When we categorize age dataset, the results of categories are not integers, which leads to the abnormal categories e. g. , category Children is from 0. 99 years old to 17. 97 years old. Our main perspective is to validate our approach using a formal evaluation process to assess how the fuzzy membership function helps a user categorizing quantities. The evaluation includes three steps: 1) manual categories creation; 2) using fuzzy membership function and 3) post-study questionnaire. In manual categories creation, investigating How does a user create categories for datasets such as the characters in The Simpsons would be a major question to be answered as in this paper we only reported on manually created to illustrate our approach.
CONCLUSION This paper introduced an interactive visualization technique to assist a user in categorizing quantities into categories. We relied upon a well-known function, the fuzzy membership function from Fuzzy Logic Theory, which we implemented as an interactive prototype. We illustrated its use for 3 case studies: age, temperature, and taxi speed data. As the prototype enables an explicit mapping of the categorization function, we plan to use it to trace the process a user follows when creating categories. In particular to understand if there is a consensus between groups of users regarding the choice of categories values interval, labeling, and confidence. We also plan to use other interactive functions to communicate this mapping, e. g. , as an interactive legend  (Park and Park, 2010b)  for both visual communication and exploration of datasets.
Acknowledgements. The authors would like to thank  Benjamin Crinquand ,  Lorenzo Sironi , and the referee  Andrei Bykov  for valuable comments regarding this work, and  Gilles Henri  for drawing our attention to the effect of expansion. This project has received funding from the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation programme  (grant agreement No  863412 ). Computing resources were provided by  TGCC  and  CINES  under the allocation A0090407669 made by  GENCI.
2h ) and in Trpm4 -/-motoneurons (data not shown). Therefore, at a concentration commonly used to block Trpm4 channels, 9-phenanthrol prevented bistable behaviors through a side-effect on voltage-gated Ca 2+ channels. We next explored the functional significance of Trpm5 channels. We assessed their role by using the Trpm5 opener linoleic acid [L. A. , 30-50 µM, ref. 40  ] and the Trpm5 blocker triphenylphosphine oxide [TPPO, 30-50 µM, ref. 41  ]. The amplitude of the sADP increased with L. A. (Fig. 2a ), while TPPO had opposite effects (Fig. 2b ). Noteworthy, the two drugs did not affect Ca 2+ spikes although input resistance was increased with TPPO (Supplementary Fig. 3a, b ). The specificity of L. A. and TPPO to Trpm5 channels was confirmed by the lack of effects of the two drugs on both Ca 2+ spikes and the sADP recorded from Trpm5 -/-mice (Supplementary Fig.
Each circle represents an individual motoneuron. h Superimposition of voltage traces recorded in normal aCSF (i. e. , without TTX and TEA) in response to a 2-s depolarizing pulse before and after reducing the temperature of the bath from 33 to 23 °C. i, j Group mean quantification of the proportion of bistable motoneurons (i) and of the bistability range ΔV (j) as a function of temperature (n = 13 mice). Numbers in brackets indicate the numbers of recorded motoneurons. n. s. , no significance; *P < 0. 05; **P < 0. 01; ***P < 0. 001 (one-way ANOVA with multiple comparisons for c, d; two-tailed Wilcoxon paired test for e-g; two-tailed Fisher test for i; two-tailed Mann-Whitney test for j). Mean ± SEM. For detailed P values, see Source data. Source data are provided as a Source data file. See also Supplementary Fig.
To avoid possible effects on rhythm-generating networks mainly located at L2, drugs targeting Trpm5 channels were applied to motoneuron pools caudally located (Fig. 6f ). A similar decrease of locomotor outputs in the L5 compartment superfused with TPPO was observed suggesting that Trpm5 channels are functionally activated in motoneurons during locomotor circuit activity in vitro. Note that the spinal cords isolated from neonatal Trpm5 -/-mice exhibited a quite normal alternating locomotor pattern (Supplementary Fig. 7c ). Together, these data indicate that Trpm5 channels are dispensable for the locomotor rhythm generation and coordination, but their activation at the level of motoneurons amplifies locomotor outputs. Role of Trpm5 in motor behaviors. Adult Trpm5 -/-mice appeared healthy with grossly normal home cage behavior but neonatal Trpm5 -/-mice displayed a weaker ability to flip from a supine position (Fig.
5 µM, n = 2 mice), dantrolene (c, d, 30 µM, n = 5 mice), caffeine (e, f, 30 µM-5 mM, n = 5 mice), chelerythrin (g, 10 µM, n = 3 mice), or thapsigargin (h, 1 µM, n = 3 mice), right: quantification of the area and/or amplitude of the sADP (a-c, e, g, h) or of the ΔV (d, f) defined as the difference between the most depolarized pre-stimulus holding potential and the most hyperpolarized holding potential for which self-sustained firing can be triggered (see Supplementary Fig. 1 ). Numbers in brackets indicate the numbers of recorded motoneurons. n. s. , no significance; *P < 0. 05; **P < 0. 01 (two-tailed Wilcoxon paired test). Mean ± SEM. For detailed P values, see Source data. Source data are provided as a Source data file. See also Supplementary Fig. 6. hindlimbs suggesting that the self-sustained discharge is a cellular correlate of the postural tone.
Assessment of motor behaviors Walking. The CatWalkXT (Noldus Information Technology, Netherlands) was used to measure walking performance. Each animal walked freely through a corridor on a glass walkway illuminated with beams of light from below. A successful walking trial was defined as having the animal walk at a steady speed (no stopping, rearing, or grooming), and three to five successful trials were collected per animal. The footprints were recorded using a camera positioned below the walkway, and footprint classification was manually corrected to ensure accurate readings. The paw print parameters were then analyzed using the CatWalk software (see data analysis). Surface righting reflex. In this test, animals were maintained in a supine position for ~1 s and then released. The performance corresponded to the time spent to recover a complete prone position (four paws in contact with the plane testing surface with a cutoff period fixed at 120 s).
Both antibodies were diluted in the blocking solution with 0. 2% triton X-100 (1:100 and 1:1000 for anti-ChAT and anti-GFAP, respectively). Slides were then washed 3 × 5 min in PBS and incubated for 2 h with an Alexa Fluor® Plus 555-anti-goat IgG secondary antibody (Invitrogen, A32816 from donkey) diluted (1:400) in the blocking solution. After 3 washes of 5 min in PBS, they were mounted with a gelatinous aqueous medium. Images were acquired using a confocal microscope (LSM700, Zeiss) equipped with a ×40 oil objective and processed with the Zen 2. 6 software (Zeiss).
The yellow solid line represents the Vaseline barrier separating the rostral (L2) from the caudal (L5) segments. g Ventral root recordings of NMA/ 5-HT-induced rhythmic activity generated before and after adding triphenylphosphine oxide (TPPO, 30 µM, n = 6 mice) to caudal lumbar segments. h Quantification of locomotor burst parameters. n. s. , no significance; *P < 0. 05; ***P < 0. 001 (fit comparison for d, e; two-tailed Wilcoxon paired test for h). Mean ± SEM. For detailed P values, see Source data. Source data are provided as a Source data file. See also Supplementary Fig. 7. m V,T variable is described as     The modifications of the above model comprised in decomposition of the total J TRPM5 current into three monovalent ion components, Na + , K + , and Cs + (J TRPM5 = J TRPM5,Na + J TRPM5,K + J TRPM5,Cs ), for which the reported channel relative permeability is approximately equal and significantly exceeds that to Ca 2+ and Mg 2+ , namely P Na :P K :P Cs = 1:1:1 » P Ca , (P Ca /P Na = 0.