ወደ ዋና ይዘት እለፍ
OpenAI

30 ጁን 2026

በGenebench-Pro ውስጥ

መመዘኛውን፣ ጥያቄዎቹን እና ደጋፊ ቁሳቁሶቹን በቅርብ ዕይታ።

የጉዳይ ጥናቶች

እነዚህ 10 የኬዝ ጥናቶች ከGeneBench-Pro የተወካዩ ጥያቄዎችን ያሳያሉ። እያንዳንዱ የኬዝ ጥናት መነሻ ጥያቄ፣ የውሂብ ስብስቦችን እና ደጋፊ ቁሳቁሶችን ያካትታል። ስለ መለኪያው አጠቃላይ ዕይታ እና ዋና ግኝቶች፣ የማስታወቂያ ብሎጉን ይመልከቱ።

ማስታወሻ፦ የፋይል ቅድመ ዕይታዎች ከሙሉ የውሂብ ስብስቦች የተወሰዱ ቅንጭቦችን ያሳያሉ።

የኬዝ ጥናት 1

ሶማቲክ ኦንኮሎጂ፦ በመዋቅራዊ ተለዋጭነት የሚመራ የዕጢ ሕክምና የጥቅም-አደጋ ውሳኔ

TXR1ን የሚያነጣጥር ሲንተቲክ፣ የዒላማው ንቃት በመዋቅራዊ ተለዋጭ በሚነዳባቸው ዕጢዎች ውስጥ አዎንታዊ ክሊኒካዊ ጥቅም እንዳለው ይገምቱ። TXR1፣ TXR1i፣ DLR1፣ እና የስታር-አሌል መለያዎች ሲንተቲክ የመለኪያ መለያዎች ናቸው። 

የዒላማው ንዑስ ቡድን፣ ጥቅምና መርዛማነት እንደ የሕክምና ውሳኔ ከመተርጎማቸው በፊት፣ ከረጅም-ንባብ፣ ከጂን ኤክስፕረሽን፣ ከእጢ-ጥራት እና ከፋርማኮጂኖሚክ ማስረጃዎች መልሶ መለየት አለበት።

ለሞዴሉ የታየው የተለቀቀ እርምጃ

A molecular tumor board registry contains trial-eligible advanced solid-tumor cases considered for a TXR1-directed inhibitor. Estimate, for tumors with SV-driven TXR1 target-mediated activation at time zero, the marginal effect of TXR1i versus non-TXR1 systemic therapy on week-16 clinical benefit as if all patients had an assessable week-16 visit. Also estimate the 8-week treatment-limiting toxicity/discontinuation risk under TXR1i in the same target population. Report net clinical utility = benefit risk difference (percentage points) - 0.35 * toxicity risk (percentage points), and choose therapy_class_code 1 if TXR1i has positive net utility and 0 otherwise. 

Use percentage-point units for all non-code quantities. Positive benefit means TXR1i improves week-16 clinical benefit relative to non-TXR1 systemic therapy.

These data came from a real experiment; you will be graded not just on numerical correctness but the quality of analytical reasoning you exhibit; do not attempt to take any shortcuts.

Return your final answer as exactly one JSON object.
Do not wrap the JSON in markdown.
Do not add prose before or after the JSON.
Do not omit any keys shown in the example.
Return the JSON object in your final answer:

JSON

1
{
2
  "answer": {
3
    "therapy_class_code": <int>,
4
    "benefit_rd_pp": <float>,
5
    "toxicity_dropout_risk_pp": <float>,
6
    "net_clinical_utility_pp": <float>
7
  },
8
  "reasoning": "<description of method and QC>"
9
}

ለሞዴሉ የቀረቡ ፋይሎች

የኬዝ ጥናት 2

ተግባራዊ ጂኖሚክስ፦ CRISPR ዒላማ ማረጋገጫ፦ lncRNA ትራንስክሪፕት ወይስ ጂኖሚክ ሎከስ?

በውጫዊ መልኩ የሚታይ የlncRNA ጥገኝነት ትራንስክሪፕት-ተኮር መሆኑን ወይም በአቅራቢያ ባለ ሎከስ እና በጎረቤት ጂን ተጽዕኖዎች የሚነሳ መሆኑን ይወስኑ።።

በትራንስክሪፕት የሚመራ ማስረጃ ለአካባቢያዊ የDNA ሎከስ መዛባት፣ ለአጎራባች ጂን መገታት፣ ለመመሪያ መቀያየሮች፣ ለGC መርዛማነት፣ እና ለፕሌት ተጽዕኖዎች የሚደረጉ መቆጣጠሪያዎችን መቋቋም አለበት።

ለሞዴሉ የታየው የተለቀቀ እርምጃ

You are given pooled CRISPRi screening data, guide-level local expression measurements, transcript-targeting CasRx follow-up data, and single-guide follow-up growth measurements for a nominated lncRNA program (LINC473) and a nearby coding gene (KIN1). The identifiers LINC473, KIN1, and ANKRD42 are synthetic benchmark labels; any resemblance to real human genes is coincidental.

Estimate the requested quantities.

Definitions:

  • lncrna_specific_lfc: the pooled-screen matched-control day-10 log2 growth effect expected at 100% effective knockdown of the dominant LINC473 transcript, not local DNA-locus effects.

  • neighbor_mediated_lfc: the pooled-screen matched-control day-10 log2 growth effect expected at 100% KIN1 repression in the local LINC473-locus model after accounting for concomitant LINC473 transcript knockdown.

  • advance_target: 1 if the evidence supports advancing LINC473 as a transcript-directed target, else 0.

Conventions:

  • all growth effects are log2(day10/day0) competitive-growth effects relative to matched controls;

  • more negative numbers indicate stronger loss of fitness;

  • set advance_target to 1 only if lncrna_specific_lfc <= -0.08 and neighbor_mediated_lfc > -0.25; otherwise 0.

These data came from a real experiment; you will be graded not just on numerical correctness but the quality of analytical reasoning you exhibit; do not attempt to take any shortcuts.

Return your final answer as exactly one JSON object.
Do not wrap the JSON in markdown.
Do not add prose before or after the JSON.
Do not omit any keys shown in the example.
Return the JSON object in your final answer:

JSON

1
{
2
  "answer": {
3
    "advance_target": <int>,
4
    "lncrna_specific_lfc": <float>,
5
    "neighbor_mediated_lfc": <float>
6
  },
7
  "reasoning": "<description of method and QC>"
8
}

ለሞዴሉ የቀረቡ ፋይሎች

የኬዝ ጥናት 3

ስታቲስቲካዊ ጄኔቲክስ፦ በተያያዘ ጄኔቲካዊ ሎከስ ውስጥ የፕሮቲን መድሃኒት ዓላማዎችን በቅድሚያ ማስቀመጥ

የአሰይ ልኬትን፣ የአሊል ኦሪየንቴሽንን፣ የአሸናፊው እርግማንን፣ LD እና ቀሪ አካባቢያዊ ፕሊዮትሮፒን በመቆጣጠር፣ cis ባለብዙ-ተለዋዋጭ የሜንደሊያን የዘፈቀደ ምደባ (cis-MVMR) በመጠቀም ለሁለት በቅርብ ያሉ ፕሮቲኖች ቀጥተኛ የበሽታ ተጽዕኖዎችን ይገምቱ።

ሁለቱ ፕሮቲኖች ተዛማጅ ሎከስ ይጋራሉ። ትንታኔው ከገደብ ተያያዥነቶች ወደ በሁኔታ የተመሠረቱና የLD ግንዛቤ ያላቸው የበሽታ ተጽዕኖዎች በአንደኛ የፕሮቲን ልኬት ላይ መንቀሳቀስ አለበት።

ለሞዴሉ የታየው የተለቀቀ እርምጃ

You are given association summary statistics and metadata for two nearby proteins (PROTA and PROTB), a binary disease outcome, a locus correlation reference, and protein measurement records.

Goal: estimate the direct log-odds effect of each protein on the disease outcome per +1 SD increase in log10 concentration, conditional on the other protein.

Interpretation: theta_PROTA and theta_PROTB use the same log-odds per-SD scale defined in the goal.

These data came from a real experiment; you will be graded not just on numerical correctness but the quality of analytical reasoning you exhibit; do not attempt to take any shortcuts.

Return your final answer as exactly one JSON object.
Do not wrap the JSON in markdown.
Do not add prose before or after the JSON.
Do not omit any keys shown in the example.
Return the JSON object in your final answer:

JSON

1
{
2
  "answer": {
3
    "theta_PROTA": <float>,
4
    "theta_PROTB": <float>
5
  },
6
  "reasoning": "<description of method and QC>"
7
}

ለሞዴሉ የቀረቡ ፋይሎች

የኬዝ ጥናት 4

ክሊኒካዊ ጂኖሚክስ / ተሸካሚነት ማጣሪያ፦ በCNV እና በሲዩዶጂን ካሊብሬሽን መሠረት የDRX1 ተሸካሚነት ማጣሪያ ቀሪ አደጋ

ከተሸካሚነት ማጣሪያ አሰይ ውሂብ በመነሳት፣ የዘር መነሻ ተኮር ተሸካሚነት ድግግሞሾችን፣ ከአሉታዊ ማጣሪያ ውጤት በኋላ የሚቀር አደጋን፣ የአጋር ተሸካሚነት ድግግሞሽን፣ እና በበሽታው የተጎዳ ፅንስ የመፈጠር አደጋን ይገምቱ።

የቀሪ አደጋ ግምት በሲዩዶጂንን ግንዛቤ ውስጥ ባስገቡ የተሸካሚነት ጥሪዎች፣ በመሥራች-ሃፕሎታይፕ ማጠቃለል፣ በዘር መነሻ ተኮር የአሰይ መለኪያ ማስተካከያ፣ እና ከተመረመሩ አጋሮች ወደ ሙሉው የአጋሮች ዝርዝር በሚደረግ የመደበኛነት ማስያዝ ላይ ይመሠረታል።

ለሞዴሉ የታየው የተለቀቀ እርምጃ

Using cohort_roster.tsv.gz, partner_roster.tsv.gz, calibration_controls.tsv.gz, target_metadata.tsv.gz, and assay_observations.tsv.gz, estimate residual reproductive risk for an autosomal recessive DRX1 condition. Report all quantities on the probability scale, not as percentages: carrier_frequency_afr and carrier_frequency_eur among screening-roster adults; residual_carrier_risk_afr_negative for an AFR screening-roster adult with a negative DRX1 screen; partner_carrier_frequency_full_roster for a uniformly sampled partner_roster.tsv.gz row; and couple_reproductive_risk for an affected conceptus when the index person is AFR and screen-negative and the partner is drawn from partner_roster.tsv.gz. Assume autosomal recessive inheritance with a 1/4 affected-conceptus risk conditional on both biological parents being carriers. 

These data came from a real experiment; you will be graded not just on numerical correctness but the quality of analytical reasoning you exhibit; do not attempt to take any shortcuts.

Return your final answer as exactly one JSON object.
Do not wrap the JSON in markdown.
Do not add prose before or after the JSON.
Do not omit any keys shown in the example.
Return the JSON object in your final answer:

JSON

1
{
2
  "answer": {
3
    "carrier_frequency_afr": <float>,
4
    "carrier_frequency_eur": <float>,
5
    "residual_carrier_risk_afr_negative": <float>,
6
    "partner_carrier_frequency_full_roster": <float>,
7
    "couple_reproductive_risk": <float>
8
  },
9
  "reasoning": "<description of method and QC>"
10
}

ለሞዴሉ የቀረቡ ፋይሎች

የኬዝ ጥናት 5

ነጠላ-ሕዋስ ጂኖሚክስ፦ ከአምቢየንት RNA ማስተካከያ በኋላ የተነቃቃ ሞኖሳይት eQTL

ከነጠላ-ሕዋስ RNA-seq ውሂብ አካባቢያዊ RNA እና ቴክኒካዊ ብክለትን ካስወገዱ በኋላ፣ በተነቃቁ ሞኖሳይቶች ውስጥ ያለው ኤክስፕረሽን ላይ የጂኖታይፕ ተጽዕኖን ይገምቱ።

አምቢየንት RNA የዒላማ ኤክስፕረሽንን እና የማንቃት ሁኔታን ለመወሰን የሚጠቀሙበትን የማርከር ፓነል ስለሚነካ፣ ማስተካከያው ከeQTL ሞዴል በፊት መከናወን አለበት።

ለሞዴሉ የታየው የተለቀቀ እርምጃ

Estimate the per-allele log rate ratio for CXCL10 expression in the activated monocyte subpopulation from the provided single-cell RNA-seq data. 

These data came from a real experiment; you will be graded not just on numerical correctness but the quality of analytical reasoning you exhibit; do not attempt to take any shortcuts.

Return your final answer as exactly one JSON object.
Do not wrap the JSON in markdown.
Do not add prose before or after the JSON.
Do not omit any keys shown in the example.
Return the JSON object in your final answer:

JSON

1
{
2
  "answer": {
3
    "beta_activated": <float>
4
  },
5
  "reasoning": "<description of method and QC>"
6
}

ለሞዴሉ የቀረቡ ፋይሎች

የኬዝ ጥናት 6

መዋቅራዊ ጄኔቲክስ፦ የተካተተ መዋቅራዊ ተለዋጭ፦ የኤክስፕረሽን ድጋፍ እና ክሊኒካዊ ግንኙነት

በስም-አልባ ኢንቨርዥን-መሰል ሎከስ ውስጥ ያለ የተጠላለፈ መዋቅራዊ ንዑስ-ሃፕሎታይፕ ካሊብሬት የተደረገ ክሊኒካዊ ተዛማጅነት እና አስተማማኝ የኤክስፕረሽን ድጋፍ እንዳለው ይገምቱ።

የተጠላለፈ የቅጂ-መጠን ምልክት በሰፊው የኢንቨርዥን አቅጣጫ ሊደበላለቅ ስለሚችል፣ የመጠን ካሊብሬሽን፣ የኤክስፕረሽን ድጋፍ እና ክሊኒካዊ ሞዴሊንግ ተለያይተው መቆየት አለባቸው።

ለሞዴሉ የታየው የተለቀቀ እርምጃ

Analyze the released files for anonymous Locus Q. Estimate the full-cohort source-population clinical association and molecular expression support for the calibrated nested segment-B structural copy dosage, separating the nested segment-B dosage from the broader outer-orientation dosage. Report subhap_log_or as the natural-log source-population total-effect odds ratio for case status per additional calibrated segment-B copy. Report expression_log_fc as the natural-log expression fold-change per calibrated segment-B copy for the expression-supported gene. Report target_support_code as 1 if the supported gene has a positive expression_log_fc and the clinical association is protective (subhap_log_or < 0), otherwise 0. Report n_calibrated_carriers as the number of reliable breakpoint-panel samples carrying at least one segment-B copy. 

These data came from a real experiment; you will be graded not just on numerical correctness but the quality of analytical reasoning you exhibit; do not attempt to take any shortcuts.

Return your final answer as exactly one JSON object.
Do not wrap the JSON in markdown.
Do not add prose before or after the JSON.
Do not omit any keys shown in the example.
Return the JSON object in your final answer:

JSON

1
{
2
  "answer": {
3
    "n_calibrated_carriers": <int>,
4
    "target_support_code": <int>,
5
    "expression_log_fc": <float>,
6
    "subhap_log_or": <float>
7
  },
8
  "reasoning": "<description of method and QC>"
9
}

ለሞዴሉ የቀረቡ ፋይሎች

የኬዝ ጥናት 7

የቁጥጥር ጂኖሚክስ፦ ከመዋቅራዊ ተለዋጮችና ከማፒንግ አርቲፋክቶች መሸፈን በኋላ የክሮማቲን ሉፕ ጥንካሬን መለካት

ከሚጠበቀው የእውቂያ ዳራ ውስጥ የዝቅተኛ ዝቅተኛ ማፕ የመደረግ ችሎታ እና የመዋቅራዊ ተለዋጭነት አርቲፋክቶችን ካስወገዱ በኋላ፣ በተወሰነ ቦታ ያለውን የኬዝ-ኮንትሮል Hi-C ሉፕ ጥንካሬ ልዩነት መጠን ይለኩ።

ዒላማው ሉፕ በ20 kb ጥራት ይገለጻል፣ ነገር ግን ዝቅተኛ ማፕ የመደረግ ችሎታ ያላቸው ንክኪዎች እና ለኬዝ ብቻ ያለ SV ስትራይፕ መጀመሪያ ካልተሸፈኑ በስተቀር፣ የተጠበቀው ንክኪ ሞዴል ይቀየራል።

ለሞዴሉ የታየው የተለቀቀ እርምጃ

You are given Hi-C contact matrices at 20 kb and 40 kb resolution plus bin annotations. Estimate the loop enrichment at the 20 kb interaction between `bin_id = 8` and `bin_id = 17` in `bins_20kb.tsv.gz`. Report three quantities: `case_loop_strength` (mean log2(observed/expected) across case replicates), `control_loop_strength` (mean log2(observed/expected) across control replicates), and `delta_loop_strength` (case minus control).

These data came from a real experiment; you will be graded not just on numerical correctness but the quality of analytical reasoning you exhibit; do not attempt to take any shortcuts.

Return your final answer as exactly one JSON object.
Do not wrap the JSON in markdown.
Do not add prose before or after the JSON.
Do not omit any keys shown in the example.
Return the JSON object in your final answer:

JSON

1
{
2
  "answer": {
3
    "case_loop_strength": <float>,
4
    "control_loop_strength": <float>,
5
    "delta_loop_strength": <float>
6
  },
7
  "reasoning": "<description of method and QC>"
8
}

ለሞዴሉ የቀረቡ ፋይሎች

የኬዝ ጥናት 8

ስታቲስቲካዊ ጄኔቲክስ፦ ባለ ብዙ ወላጆች የQTL ካርታ ማስተካከያ ከመሥራች እንደገና ግንባታ ጋር

የፊኖታይፕ ተዛማጅነትን ከመፈተሽ በፊት የመስራቾችን የዘር-መነሻ በመልሶ ግንባታ፣ በስምንት-መስራች ዳግም-የተዋሃደ ህዝብ ውስጥ ያለውን የክሮሞሶም-1 የመጠናዊ-ባህሪ ሎከስ ማፕ ያድርጉ።

የሚታዩት የማርከር ውሂቦች ሁለት-አሊል ያላቸው ናቸው፣ ነገር ግን ባዮሎጂያዊው ምልክት የመስራች ዘር መነሻ ነው። ስለዚህ፣ ሊከላከል የሚችል ትንተና የመስራች ሁኔታን እንደገና መገንባት፣ የማርከር አቅጣጫን ማረጋገጥ፣ እና QTLን ከባች ጋር ከተሰለፈ አደናቃፊ ጫፍ መለየት አለበት።

ለሞዴሉ የታየው የተለቀቀ እርምጃ

Map the chromosome 1 QTL in an 8-founder multi-parent population. Report the position (cM) and which founder carries the high-effect allele.

Report high_founder as "F1".."F8".

These data came from a real experiment; you will be graded not just on numerical correctness but the quality of analytical reasoning you exhibit; do not attempt to take any shortcuts.

Return your final answer as exactly one JSON object.
Do not wrap the JSON in markdown.
Do not add prose before or after the JSON.
Do not omit any keys shown in the example.
Return the JSON object in your final answer:

JSON

1
{
2
"answer": {
3
"high_founder": "<string>",
4
"qtl_pos_cM": <float>
5
},
6
"reasoning": "<description of method and QC>"
7
}

Data files:

  • markers.tsv.gz: marker metadata

  • founders.tsv.gz: founder alleles at each marker

  • ril_genotypes.npz: observed RIL genotypes (biallelic)

  • phenotypes.tsv.gz: phenotype and covariates

ለሞዴሉ የቀረቡ ፋይሎች

የኬዝ ጥናት 9

የሕዝብ ጄኔቲክስ፦ ለወላጅ ልዩ የዘር መነሻ እና የቅርብ ጊዜ የድብልቅ ጊዜ

ከተደጋጋሚ ስህተቶች እና ክሮሞሶም ተኮር የመለያ መገልበጥ ከተስተካከለ በኋላ፣ በሂደት ከተደረጉ የአካባቢያዊ የዘር መነሻ ክፍሎች ላይ በመመርመር ለእያንዳንዱ ወላጅ ተኮር የዘር መነሻ መጠኖችን እና በቅርቡ የተከሰተ የዘር መቀላቀል ጊዜን ይገምቱ።

የዘር መነሻ ክፍልፋዮች እና የፐልስ ጊዜዎች ሁለቱም፣ ተገላቢጦሽ የትራክት አርቲፋክቶች፣ በክሮሞሶም ውስጥ አካባቢያዊ የመለያ ኢንቨርዥን፣ ወይም የማፕ አካፋዮች በትክክል ካልተያዙ ይለዋወጣሉ።

ለሞዴሉ የታየው የተለቀቀ እርምጃ

You are given phased local-ancestry tracts for one admixed individual. Estimate, for each transmitted parental haplotype, the fraction of ancestry A across the called tract span and the number of generations since a single recent admixture pulse. Label parent1 as the haplotype with the smaller ancestry-A fraction and parent2 as the haplotype with the larger ancestry-A fraction. 

These data came from a real experiment; you will be graded not just on numerical correctness but the quality of analytical reasoning you exhibit; do not attempt to take any shortcuts.

Return your final answer as exactly one JSON object.
Do not wrap the JSON in markdown.
Do not add prose before or after the JSON.
Do not omit any keys shown in the example.
Return the JSON object in your final answer:

JSON

1
{
2
  "answer": {
3
    "parent1_A_fraction": <float>,
4
    "parent1_t": <float>,
5
    "parent2_A_fraction": <float>,
6
    "parent2_t": <float>
7
  },
8
  "reasoning": "<description of method and QC>"
9
}

ለሞዴሉ የቀረቡ ፋይሎች

የኬዝ ጥናት 10

የሕዝብ ጄኔቲክስ፦ የተዘበራረቁ የጥንታዊ DNA የጊዜ ተከታታይ መረጃዎች የምርጫ ግምገማ

ከጥንታዊ የአሊል ድግግሞሽ የጊዜ ተከታታይ ውሂብ በመነሳት፣ የአሊል አቅጣጫ-አቀማመጥን፣ የአቅጣጫ ስህተትን፣ የጄኔቲክ ድሪፍትን እና ተለዋዋጭ የሕዝብ መጠንን ከግምት ውስጥ በማስገባት፣ ከሁለት ሃፕሎይድ ሎካይ ውስጥ የትኛው በይበልጥ ጠንካራ አዎንታዊ ምርጫ ሥር እንዳለ ይገምቱ።

የተዘበራረቁ ጥንታዊ የጊዜ-ሂደት መስመሮች ሁለቱም ሎካይ በአንድ የተወሰደ-አሊል ልኬት ላይ እስኪቀመጡ እና የቀረቡት በናሙና-ደረጃ የሲክዌንሲንግ-ስህተት እሴቶች በቀጥታ ሞዴል እስኪደረጉ ድረስ በቀጥታ ሊነጻጸሩ አይችሉም።

You are given allele-frequency time series data from two haploid loci sampled over multiple generations.

One locus is under stronger positive selection than the other. Estimate the selection coefficient s for the more strongly selected locus, where s > 0 means the derived allele is favored.

Assume instrument-driven sequencing error is ~1%. The seq_error column is the average of the two directional allele-miscall rates for that locus and sample.

The selected_locus value must be "A" or "B".

These data came from a real experiment; you will be graded not just on numerical correctness but the quality of analytical reasoning you exhibit; do not attempt to take any shortcuts.

Return your final answer as exactly one JSON object.
Do not wrap the JSON in markdown.
Do not add prose before or after the JSON.
Do not omit any keys shown in the example.
Return the JSON object in your final answer:

JSON

1
{
2
"answer": {
3
"selected_locus": "<string>",
4
"s": <float>
5
},
6
"reasoning": "<description of method and QC>"
7
}

ለሞዴሉ የቀረቡ ፋይሎች